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Discourse Analysis – Methods, Types and Examples

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Discourse Analysis

Definition:

Discourse Analysis is a method of studying how people use language in different situations to understand what they really mean and what messages they are sending. It helps us understand how language is used to create social relationships and cultural norms.

It examines language use in various forms of communication such as spoken, written, visual or multi-modal texts, and focuses on how language is used to construct social meaning and relationships, and how it reflects and reinforces power dynamics, ideologies, and cultural norms.

Types of Discourse Analysis

Some of the most common types of discourse analysis are:

Conversation Analysis

This type of discourse analysis focuses on analyzing the structure of talk and how participants in a conversation make meaning through their interaction. It is often used to study face-to-face interactions, such as interviews or everyday conversations.

Critical discourse Analysis

This approach focuses on the ways in which language use reflects and reinforces power relations, social hierarchies, and ideologies. It is often used to analyze media texts or political speeches, with the aim of uncovering the hidden meanings and assumptions that are embedded in these texts.

Discursive Psychology

This type of discourse analysis focuses on the ways in which language use is related to psychological processes such as identity construction and attribution of motives. It is often used to study narratives or personal accounts, with the aim of understanding how individuals make sense of their experiences.

Multimodal Discourse Analysis

This approach focuses on analyzing not only language use, but also other modes of communication, such as images, gestures, and layout. It is often used to study digital or visual media, with the aim of understanding how different modes of communication work together to create meaning.

Corpus-based Discourse Analysis

This type of discourse analysis uses large collections of texts, or corpora, to analyze patterns of language use across different genres or contexts. It is often used to study language use in specific domains, such as academic writing or legal discourse.

Descriptive Discourse

This type of discourse analysis aims to describe the features and characteristics of language use, without making any value judgments or interpretations. It is often used in linguistic studies to describe grammatical structures or phonetic features of language.

Narrative Discourse

This approach focuses on analyzing the structure and content of stories or narratives, with the aim of understanding how they are constructed and how they shape our understanding of the world. It is often used to study personal narratives or cultural myths.

Expository Discourse

This type of discourse analysis is used to study texts that explain or describe a concept, process, or idea. It aims to understand how information is organized and presented in such texts and how it influences the reader’s understanding of the topic.

Argumentative Discourse

This approach focuses on analyzing texts that present an argument or attempt to persuade the reader or listener. It aims to understand how the argument is constructed, what strategies are used to persuade, and how the audience is likely to respond to the argument.

Discourse Analysis Conducting Guide

Here is a step-by-step guide for conducting discourse analysis:

• What are you trying to understand about the language use in a particular context?
• What are the key concepts or themes that you want to explore?
• Select the data: Decide on the type of data that you will analyze, such as written texts, spoken conversations, or media content. Consider the source of the data, such as news articles, interviews, or social media posts, and how this might affect your analysis.
• Transcribe or collect the data: If you are analyzing spoken language, you will need to transcribe the data into written form. If you are using written texts, make sure that you have access to the full text and that it is in a format that can be easily analyzed.
• Read and re-read the data: Read through the data carefully, paying attention to key themes, patterns, and discursive features. Take notes on what stands out to you and make preliminary observations about the language use.
• Develop a coding scheme : Develop a coding scheme that will allow you to categorize and organize different types of language use. This might include categories such as metaphors, narratives, or persuasive strategies, depending on your research question.
• Code the data: Use your coding scheme to analyze the data, coding different sections of text or spoken language according to the categories that you have developed. This can be a time-consuming process, so consider using software tools to assist with coding and analysis.
• Analyze the data: Once you have coded the data, analyze it to identify patterns and themes that emerge. Look for similarities and differences across different parts of the data, and consider how different categories of language use are related to your research question.
• Interpret the findings: Draw conclusions from your analysis and interpret the findings in relation to your research question. Consider how the language use in your data sheds light on broader cultural or social issues, and what implications it might have for understanding language use in other contexts.
• Write up the results: Write up your findings in a clear and concise way, using examples from the data to support your arguments. Consider how your research contributes to the broader field of discourse analysis and what implications it might have for future research.

Applications of Discourse Analysis

Here are some of the key areas where discourse analysis is commonly used:

• Political discourse: Discourse analysis can be used to analyze political speeches, debates, and media coverage of political events. By examining the language used in these contexts, researchers can gain insight into the political ideologies, values, and agendas that underpin different political positions.
• Media analysis: Discourse analysis is frequently used to analyze media content, including news reports, television shows, and social media posts. By examining the language used in media content, researchers can understand how media narratives are constructed and how they influence public opinion.
• Education : Discourse analysis can be used to examine classroom discourse, student-teacher interactions, and educational policies. By analyzing the language used in these contexts, researchers can gain insight into the social and cultural factors that shape educational outcomes.
• Healthcare : Discourse analysis is used in healthcare to examine the language used by healthcare professionals and patients in medical consultations. This can help to identify communication barriers, cultural differences, and other factors that may impact the quality of healthcare.
• Marketing and advertising: Discourse analysis can be used to analyze marketing and advertising messages, including the language used in product descriptions, slogans, and commercials. By examining these messages, researchers can gain insight into the cultural values and beliefs that underpin consumer behavior.

When to use Discourse Analysis

Discourse analysis is a valuable research methodology that can be used in a variety of contexts. Here are some situations where discourse analysis may be particularly useful:

• When studying language use in a particular context: Discourse analysis can be used to examine how language is used in a specific context, such as political speeches, media coverage, or healthcare interactions. By analyzing language use in these contexts, researchers can gain insight into the social and cultural factors that shape communication.
• When exploring the meaning of language: Discourse analysis can be used to examine how language is used to construct meaning and shape social reality. This can be particularly useful in fields such as sociology, anthropology, and cultural studies.
• When examining power relations: Discourse analysis can be used to examine how language is used to reinforce or challenge power relations in society. By analyzing language use in contexts such as political discourse, media coverage, or workplace interactions, researchers can gain insight into how power is negotiated and maintained.
• When conducting qualitative research: Discourse analysis can be used as a qualitative research method, allowing researchers to explore complex social phenomena in depth. By analyzing language use in a particular context, researchers can gain rich and nuanced insights into the social and cultural factors that shape communication.

Examples of Discourse Analysis

Here are some examples of discourse analysis in action:

• A study of media coverage of climate change: This study analyzed media coverage of climate change to examine how language was used to construct the issue. The researchers found that media coverage tended to frame climate change as a matter of scientific debate rather than a pressing environmental issue, thereby undermining public support for action on climate change.
• A study of political speeches: This study analyzed political speeches to examine how language was used to construct political identity. The researchers found that politicians used language strategically to construct themselves as trustworthy and competent leaders, while painting their opponents as untrustworthy and incompetent.
• A study of medical consultations: This study analyzed medical consultations to examine how language was used to negotiate power and authority between doctors and patients. The researchers found that doctors used language to assert their authority and control over medical decisions, while patients used language to negotiate their own preferences and concerns.
• A study of workplace interactions: This study analyzed workplace interactions to examine how language was used to construct social identity and maintain power relations. The researchers found that language was used to construct a hierarchy of power and status within the workplace, with those in positions of authority using language to assert their dominance over subordinates.

Purpose of Discourse Analysis

The purpose of discourse analysis is to examine the ways in which language is used to construct social meaning, relationships, and power relations. By analyzing language use in a systematic and rigorous way, discourse analysis can provide valuable insights into the social and cultural factors that shape communication and interaction.

The specific purposes of discourse analysis may vary depending on the research context, but some common goals include:

• To understand how language constructs social reality: Discourse analysis can help researchers understand how language is used to construct meaning and shape social reality. By analyzing language use in a particular context, researchers can gain insight into the cultural and social factors that shape communication.
• To identify power relations: Discourse analysis can be used to examine how language use reinforces or challenges power relations in society. By analyzing language use in contexts such as political discourse, media coverage, or workplace interactions, researchers can gain insight into how power is negotiated and maintained.
• To explore social and cultural norms: Discourse analysis can help researchers understand how social and cultural norms are constructed and maintained through language use. By analyzing language use in different contexts, researchers can gain insight into how social and cultural norms are reproduced and challenged.
• To provide insights for social change: Discourse analysis can provide insights that can be used to promote social change. By identifying problematic language use or power imbalances, researchers can provide insights that can be used to challenge social norms and promote more equitable and inclusive communication.

Characteristics of Discourse Analysis

Here are some key characteristics of discourse analysis:

• Focus on language use: Discourse analysis is centered on language use and how it constructs social meaning, relationships, and power relations.
• Multidisciplinary approach: Discourse analysis draws on theories and methodologies from a range of disciplines, including linguistics, anthropology, sociology, and psychology.
• Systematic and rigorous methodology: Discourse analysis employs a systematic and rigorous methodology, often involving transcription and coding of language data, in order to identify patterns and themes in language use.
• Contextual analysis : Discourse analysis emphasizes the importance of context in shaping language use, and takes into account the social and cultural factors that shape communication.
• Focus on power relations: Discourse analysis often examines power relations and how language use reinforces or challenges power imbalances in society.
• Interpretive approach: Discourse analysis is an interpretive approach, meaning that it seeks to understand the meaning and significance of language use from the perspective of the participants in a particular discourse.
• Emphasis on reflexivity: Discourse analysis emphasizes the importance of reflexivity, or self-awareness, in the research process. Researchers are encouraged to reflect on their own positionality and how it may shape their interpretation of language use.

Advantages of Discourse Analysis

Discourse analysis has several advantages as a methodological approach. Here are some of the main advantages:

• Provides a detailed understanding of language use: Discourse analysis allows for a detailed and nuanced understanding of language use in specific social contexts. It enables researchers to identify patterns and themes in language use, and to understand how language constructs social reality.
• Emphasizes the importance of context : Discourse analysis emphasizes the importance of context in shaping language use. By taking into account the social and cultural factors that shape communication, discourse analysis provides a more complete understanding of language use than other approaches.
• Allows for an examination of power relations: Discourse analysis enables researchers to examine power relations and how language use reinforces or challenges power imbalances in society. By identifying problematic language use, discourse analysis can contribute to efforts to promote social justice and equality.
• Provides insights for social change: Discourse analysis can provide insights that can be used to promote social change. By identifying problematic language use or power imbalances, researchers can provide insights that can be used to challenge social norms and promote more equitable and inclusive communication.
• Multidisciplinary approach: Discourse analysis draws on theories and methodologies from a range of disciplines, including linguistics, anthropology, sociology, and psychology. This multidisciplinary approach allows for a more holistic understanding of language use in social contexts.

Limitations of Discourse Analysis

Some Limitations of Discourse Analysis are as follows:

• Time-consuming and resource-intensive: Discourse analysis can be a time-consuming and resource-intensive process. Collecting and transcribing language data can be a time-consuming task, and analyzing the data requires careful attention to detail and a significant investment of time and resources.
• Limited generalizability: Discourse analysis is often focused on a particular social context or community, and therefore the findings may not be easily generalized to other contexts or populations. This means that the insights gained from discourse analysis may have limited applicability beyond the specific context being studied.
• Interpretive nature: Discourse analysis is an interpretive approach, meaning that it relies on the interpretation of the researcher to identify patterns and themes in language use. This subjectivity can be a limitation, as different researchers may interpret language data differently.
• Limited quantitative analysis: Discourse analysis tends to focus on qualitative analysis of language data, which can limit the ability to draw statistical conclusions or make quantitative comparisons across different language uses or contexts.
• Ethical considerations: Discourse analysis may involve the collection and analysis of sensitive language data, such as language related to trauma or marginalization. Researchers must carefully consider the ethical implications of collecting and analyzing this type of data, and ensure that the privacy and confidentiality of participants is protected.

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Exploring the role of discourse in marketing and consumer research

2014, Journal of Consumer Behaviour

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Exploring the role of discourse in marketing and consumer research

Summary  ( 3 min read), introduction.

• Marketing and consumption depend largely on discourse for the creation, ordering, dissemination and reinforcement of product knowledge.
• In its modern reconfiguration marketing and consumer research theory has, the authors would argue, been less compatible with discourse based readings because of the ontological status of the consumer as a sovereign, autonomous and individuated agency who has freedom to act in accordance with his or her own interests in the market.
• Critical marketing offers a number of appealing directions for discourse based readings although controversial questions remain over the extent to which the distance that critical marketers seek to establish is actually a separation of some sorts.
• The authors intention in this paper is to advance the use of discourse analysis both as a critical mirror and methodological lens for marketing and consumer researchers.
• Upon this broad conception of discourse the authors set about to introduce, position, distinguish and develop discourse analysis as a pathway to disciplinary reflexivity and empirical insight.

Consumption and markets as text

• There was a growing interest in discourse based approaches among some consumer researchers and, to a lesser extent marketing research, in the 1980s and 1990s, following and mirroring a much broader trend in the social sciences and humanities.
• This broad movement sought to focus analysis on a range of text and discourse practices, including text production, dissemination and   10   communication, and consumption.
• This preference for analysing advertising text is probably a major factor that has limited the development of more varied approaches to discourse and discourse analysis in other areas of consumer research such as considering other types of text and broader notions of discourse beyond the study of advertisements (Humphreys, 2010a; Kelly et al., 2005).
• A recurring tension however remains around how to conceptualise and render the power of discourse to shape and frame consumer experience on the one hand (for example Tuncay   14   Zayer et al 2012), and the capacity of consumers to utilise the opportunities made possible by the fluid potentiality of discourse to actualise their own identities.
• Discourse Analysis demonstrates and re-emphasises clear synergies and links within marketing academia, especially between Critical marketing, macromarketing and consumer culture theory.

Orientating Discourse Analysis to Marketing and Consumer Research

• There are a variety of styles and uses of discourse analysis (Alvesson and Karreman.
• This section seeks to illuminate three key approaches, distinguished by their technical, constitutive and political research orientations (Table 1), and elaborating on the possible ways they might be employed in marketing (Table 2).
• The rationale for this relational categorisation is that discourse constitutes knowledge of subjects in relationships and that, similarly, discourse is both content and relational context (Boje at al., 2004).
• Interpretations of marketing/consumer discourse do not stand alone from the relational contexts in which they are situated.

Technical orientation to DA

• First, associated with ethnomethodology and conversation analysis, are approaches where discourse is taken as a technical interaction produced in the skilled accomplishment of everyday social life (Garfinkel, 1967; Gergen 1999; Goffman, 1974; Schegloff, 1992; Sinclair and Coultard, 1975).
• The unit of analysis – commonly, but not exclusively, ‘talk’ – is examined through a technical, micro-linguistic lens (Schegloff, 1992), identifying the rules that govern the organisation of talk such as “speech rights” and “turn-taking” (i.e. who may talk next and when).
• Consumer researchers would be attuned to grammatical structures like cues, turn-taking, discourse markers (but, however), personal pronouns (me, I), as well as more complex linguistic forms such as juxtapositions (good/bad), rhetorical devices, metaphors (linking concepts), metonyms and even narratives (ideal story types) that organise local consumer texts.
• These linguistic features are interpreted for the organising function they play in certain market relationships.

Constitutive orientation to DA

• The second cluster of DA picks up on this observation that discourse not only creates rules of talk in local texts but is constitutive of social reality (Berger and Luckmann, 1971; Potter and Wetherell, 1987; Wetherell, 1998).
• Analysis at this level consequently concerns the situated nature of the text under investigation, not only in terms of who it is produced by and for but how it is produced by drawing upon wider social discourses.
• Macromarketing researchers interested in how relations between marketing and society have evolved (see Fougère and Skålén 2013) can examine how historical social discourses (e.g. the ‘free market’, ‘economy’ and ‘social justice’) employed in key texts, (re-)constitute certain kinds of marketing-society relations, such as ‘social capitalism’, ‘social marketing’, ‘sustainable development’ or ‘ethical consumption’.
• How consumers integrate these discourses into their own accounts, how they use them to connect their self to or, contrastingly, disassociate their self from products, brands, corporations, and other consumers (Holt, 2002) are fruitful avenues here.
• With a concern for content-context dynamics, this orientation to DA also provides marketing research with a means to examine marketing subjectivities and relations within corporations.

Political orientation to DA

• The technical and constitutive orientations to DA can be seen as implicitly critical views in the sense that they challenge functionalist assumptions about marketing subjects independent of discourses that render them knowable in some way.
• Yet they do not begin with or focus on critical questions.
• In exploring market-society relations, for example, Schroeder and Borgerson (1999) show how marketing texts commodify Hawaii for western tourist consumers by drawing upon a dominant paradisal, neo-colonial discourses of the ‘exotic other’.

Framing Critical Discourse Analysis for Marketing

• Drawing upon contributions from sociology, consumer and organisational research.the authors.
• The interpretive context constructed in this dialectic hails to consumers (Parker, 1992), as hardworking, economically concerned patriots, to “reject climate regulation and keep filing up your cars at the pump!”.
• Power may be interpreted by analysts along different relational axes (see Table 2.) and between subjects who are present as well as those ostensibly absent from the same discourse.
• Third, they show how the consumer’s use of an ‘independent guidebook’ – a toolkit for ‘how to do’ independent tourism- paradoxically engenders dependency in tourist’s relations with the market.

Opening up consumer discourse

• Its   25   ‘de-naturalising’ agenda (Kress, 1990) renders CDA uniquely poised to help analysts understand how marketing discourse renders certain consumer realities ‘seeable’, whilst others ‘unseeable’.
• Caruana and Crane (2008), for instance, show how the marketing discourse of ‘Responsible Tourism’ depicts tourist practices and relations with local people and ecosystems as responsible, ‘trouble and guilt-free’.
• CDA can be used here to highlight paradox and contradiction as well as the processes that sustain their subversion.
• Yet at the same time, the discipline – as a conventional ‘way of knowing’ markets and ‘being marketers’ - is essentially constituted by and from a constellation of heuristic devices, concepts and definitions that reify marketing as a self-evidently natural subject (Hackley, 2003).

Conclusions

• Discourse analysis, and CDA in particular, offers a valuable methodological and epistemological direction for marketers who, while willing to subject the mainstream marketing discourse to scrutiny and analysis are also able to examine some of the reasons why dominant discourses about marketing remain powerful and widely accepted.
• This broader view opens up a whole range of   27   empirical, conceptual and ethical questions, for instance, concerning the cultural functions of various marketing texts, how consumers and marketers construct and are constructed in them, how important objects and relationships are legitimized and sustained and how power relations operate therein.
• As Humphreys (2010b) demonstrates, analysis of discourse can illustrate market-making and creation, i.e. as products of certain discourse practices.
• Djavlonbek and Varey (2013) illustrate these kinds of outcomes in their examination of green consumer behaviour, showing how meaning structures (interaction and discourse) in this context reproduce inconsistent behaviour as necessary and practical outcomes of a market structure.

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Cites background from "Exploring the role of discourse in ..."

... Discourse-based analysis provides an approach for reflecting on marketing thought, especially ‘amongst countervailing discourses’ on sustainable consumption, the environment and justice, for example (Fitchett & Caruana, 2015, p. 2). ...

... Further, discourse analysis allows a reflection and identification of the wider political and economic assumptions in marketing thought (Fitchett & Caruana, 2015). ...

... In the same vein, similar contentious concepts such as consumer–citizen divide and consumer sovereignty (Fitchett & Caruana, 2015; Sandberg & Polsa, 2015) should be reflected upon through discourse-based analysis to understand the power dynamics and various conceptualisations at play. ...

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Cites methods from "Exploring the role of discourse in ..."

... In this paper, we analyse marketing of PST through parents’ consumer narratives (Fitchett and Caruana 2015) published on the website of one of the largest PST companies in Sweden. ...

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... Multiple sources also allow a broader understanding of the phenomenon by creating informative patterns (Besley, 2015; Fitchett & Caruana, 2015; Gee, 2005; Olsson & Heizmann, 2015; Thompson, 2004; Wetherell, 1998). ...

... The concept of intertextuality importantly allows such diverse texts to be viewed relationally, which adds multiplicity of relevance (Allen, 2011; Joy & Li, 2012; Fitchett & Caruana, 2015). ...

... Reproducing social and cultural perspectives but self-structured towards on-site uses (Caruana & Crane, 2008; Thompson, 2004), which make consumers, institutions and groups behave in certain ways (Fitchett & Caruana, 2015). ...

... 3.3.8 Presentation of the Cool Self Micro-level practices also create discourses which derive from every day occurrences, although it is unclear where they originate from and who propagates them (Fitchett & Caruana, 2015). ...

... 4.3.2 Literary and Textual Analysis Literary, cultural, market and consumer texts are legitimate sources for research in CCT as they improve understanding of phenomena (Fitchett, et al., 2014; Fitchett & Caruana, 2015; Joy & Lin, 2012; Macinnes & Folkes, 2009). ...

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"Exploring the role of discourse in ..." refers background in this paper

... Technical orientation to DA First, associated with ethnomethodology and conversation analysis, are approaches where discourse is taken as a technical interaction produced in the skilled accomplishment of everyday social life (Garfinkel, 1967; Goffman, 1974; Sinclair and Coulthard, 1975; Schegloff, 1992; Gergen, 1999). ...

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Related Papers (5)

Frequently asked questions (14), q1. what are the contributions mentioned in the paper "exploring the role of discourse in marketing and consumer research" .

This paper reviews the development of discourse based analysis in marketing and consumer research and outlines the application of various forms of discourse analysis ( DA ) as an approach.   The paper locates this development alongside broader disciplinary movements and restates the potential for Critical Discourse Analysis ( CDA ) in marketing and consumer behaviour research.   The authors argue that discourse based approaches have considerable potential and application particularly in terms of supporting disciplinary reflexivity and research criticality.   The paper outlines some of the ways that discourse analysis, and especially Critical Discourse Analysis, could be developed and applied in marketing and consumer research.   The authors provide a critical review of the development of discourse and text based studies in marketing and consumer research, and show how this has shaped, framed and limited the application and utilization of discourse analysis in particular ways.   The paper offers an up to date critical reflection on the development of discourse based approaches, promoting reflexivity whilst providing empirical pathways to mainstream and critical research.  

Q2. What future works have the authors mentioned in the paper "Exploring the role of discourse in marketing and consumer research" ?

This is probably one of the most exciting and transformative aspects of CDA for marketing because it opens up the possibility of examining marketing ideology and discourse through analysis of everyday, common-place activities and processes.   Dobscha, S. and Ozanne, J. L. ( 2001 ), “ An ecofeminist analysis of environmentally friendly women using qualitative methodology: the emancipatory potential of an ecological life, ” Journal of Public Policy and Marketing, 20 ( 2 ), pp. 201-214.  

Q3. What is the purpose of this paper?

Their intention in this paper is to advance the use of discourse analysis both as a critical mirror and methodological lens for marketing and consumer researchers.  

Q4. What is the significance of discourse analysis?

The pioneering research on discourse and textual analysis became foundational to amore general cultural turn in consumer research throughout the 2000s.  

Q5. What are the disciplines of marketing and consumer behaviour?

Beyond marketing practice, the disciplines of marketing and consumer behaviour arealso naturalising and thus potentially subverting discourses.  

Q6. What is the significance of Scott’s support for reader-response?

Scott’s (1994b) support for reader-response has particular resonance because it calls back to an underlying preference in consumer and marketing research to afford some kind of priority or sovereignty to the agent-consumer (or reader).  

Q7. What is the main impediment to the uptake of discourse analysis?

An additional impediment to the uptake of discourse analysis, though not unique to marketing, is the commonly held belief in very limited views of language itself:“Language is not only content; it is also context and a way to recontextualize content.  

Q8. What is the key aspect of CDA?

A key aspect of CDA is the idea that discourses emerge from micro-level practices, orto put it another way, they are a ‘bottom up’ phenomenon that derive from everyday conditions and practices.  

Q9. What is the main reason why the literature is underrepresented in marketing and consumer research?

This   4  underrepresentation is manifest in part through resistance to the ontological view that marketing is socially constructed (Berger and Luckmann, 1971; Hackley, 2001) and in part in scepticism over language as a viable unit of analysis (Boje et al., 2004).  

Q10. What is the main purpose of the critical marketing movement?

From a Critical Management Studies perspective however, marketing is generally considered as a relatively marginal ‘specialism’ of management somewhat subordinate to the ‘core’ organizational theory, behaviour and culture (Alvesson 2011).  

Q11. What is the main point of departure?

The main point of departure here is that marketing is generally acknowledged as a culturally or socially constructed unit of analysis (Burton 2001; Hackley 2001).  

Q12. What is the real value of discourse analysis?

Though rather than wielding the ‘critical stick’ at marketing, the real value of such discourse-based approaches is that they provide a methodological tool with which to firmly anchor critical research questions about the nature and implications of marketing realities, so that they may be positively transformed (Fairclough, 1992, 1995).  

Q13. What was the need for ad-based analysis?

Only relatively minor adaptations or redefinition of the ad as text, the consumer/receiver as reader, and the agency as author/producer, was needed in order to introduce literary and text-based analysis.  

Q14. What does the term ‘discourse analysis’ mean?

Discourse analysis does not imply a deterministic or structuralist view of the world, that somehow the ‘discourse of the market’ causes people, institutions and organisations to conform and behave in certain kinds of ways.  

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What (Exactly) Is Discourse Analysis? A Plain-Language Explanation & Definition (With Examples)

By: Jenna Crosley (PhD). Expert Reviewed By: Dr Eunice Rautenbach | June 2021

Discourse analysis is one of the most popular qualitative analysis techniques we encounter at Grad Coach. If you’ve landed on this post, you’re probably interested in discourse analysis, but you’re not sure whether it’s the right fit for your project, or you don’t know where to start. If so, you’ve come to the right place.

Overview: Discourse Analysis Basics

In this post, we’ll explain in plain, straightforward language :

• What discourse analysis is
• When to use discourse analysis
• The main approaches to discourse analysis
• How to conduct discourse analysis

What is discourse analysis?

Let’s start with the word “discourse”.

In its simplest form, discourse is verbal or written communication between people that goes beyond a single sentence . Importantly, discourse is more than just language. The term “language” can include all forms of linguistic and symbolic units (even things such as road signs), and language studies can focus on the individual meanings of words. Discourse goes beyond this and looks at the overall meanings conveyed by language in context .  “Context” here refers to the social, cultural, political, and historical background of the discourse, and it is important to take this into account to understand underlying meanings expressed through language.

A popular way of viewing discourse is as language used in specific social contexts, and as such language serves as a means of prompting some form of social change or meeting some form of goal.

Now that we’ve defined discourse, let’s look at discourse analysis .

Discourse analysis uses the language presented in a corpus or body of data to draw meaning . This body of data could include a set of interviews or focus group discussion transcripts. While some forms of discourse analysis center in on the specifics of language (such as sounds or grammar), other forms focus on how this language is used to achieve its aims. We’ll dig deeper into these two above-mentioned approaches later.

As Wodak and Krzyżanowski (2008) put it: “discourse analysis provides a general framework to problem-oriented social research”. Basically, discourse analysis is used to conduct research on the use of language in context in a wide variety of social problems (i.e., issues in society that affect individuals negatively).

For example, discourse analysis could be used to assess how language is used to express differing viewpoints on financial inequality and would look at how the topic should or shouldn’t be addressed or resolved, and whether this so-called inequality is perceived as such by participants.

What makes discourse analysis unique is that it posits that social reality is socially constructed , or that our experience of the world is understood from a subjective standpoint. Discourse analysis goes beyond the literal meaning of words and languages

For example, people in countries that make use of a lot of censorship will likely have their knowledge, and thus views, limited by this, and will thus have a different subjective reality to those within countries with more lax laws on censorship.

When should you use discourse analysis?

There are many ways to analyze qualitative data (such as content analysis , narrative analysis , and thematic analysis ), so why should you choose discourse analysis? Well, as with all analysis methods, the nature of your research aims, objectives and research questions (i.e. the purpose of your research) will heavily influence the right choice of analysis method.

The purpose of discourse analysis is to investigate the functions of language (i.e., what language is used for) and how meaning is constructed in different contexts, which, to recap, include the social, cultural, political, and historical backgrounds of the discourse.

For example, if you were to study a politician’s speeches, you would need to situate these speeches in their context, which would involve looking at the politician’s background and views, the reasons for presenting the speech, the history or context of the audience, and the country’s social and political history (just to name a few – there are always multiple contextual factors).

Discourse analysis can also tell you a lot about power and power imbalances , including how this is developed and maintained, how this plays out in real life (for example, inequalities because of this power), and how language can be used to maintain it. For example, you could look at the way that someone with more power (for example, a CEO) speaks to someone with less power (for example, a lower-level employee).

Therefore, you may consider discourse analysis if you are researching:

• Some form of power or inequality (for example, how affluent individuals interact with those who are less wealthy
• How people communicate in a specific context (such as in a social situation with colleagues versus a board meeting)
• Ideology and how ideas (such as values and beliefs) are shared using language (like in political speeches)
• How communication is used to achieve social goals (such as maintaining a friendship or navigating conflict)

As you can see, discourse analysis can be a powerful tool for assessing social issues , as well as power and power imbalances . So, if your research aims and objectives are oriented around these types of issues, discourse analysis could be a good fit for you.

Discourse Analysis: The main approaches

There are two main approaches to discourse analysis. These are the language-in-use (also referred to as socially situated text and talk ) approaches and the socio-political approaches (most commonly Critical Discourse Analysis ). Let’s take a look at each of these.

Approach #1: Language-in-use

Language-in-use approaches focus on the finer details of language used within discourse, such as sentence structures (grammar) and phonology (sounds). This approach is very descriptive and is seldom seen outside of studies focusing on literature and/or linguistics.

Because of its formalist roots, language-in-use pays attention to different rules of communication, such as grammaticality (i.e., when something “sounds okay” to a native speaker of a language). Analyzing discourse through a language-in-use framework involves identifying key technicalities of language used in discourse and investigating how the features are used within a particular social context.

For example, English makes use of affixes (for example, “un” in “unbelievable”) and suffixes (“able” in “unbelievable”) but doesn’t typically make use of infixes (units that can be placed within other words to alter their meaning). However, an English speaker may say something along the lines of, “that’s un-flipping-believable”. From a language-in-use perspective, the infix “flipping” could be investigated by assessing how rare the phenomenon is in English, and then answering questions such as, “What role does the infix play?” or “What is the goal of using such an infix?”

Need a helping hand?

Approach #2: Socio-political

Socio-political approaches to discourse analysis look beyond the technicalities of language and instead focus on the influence that language has in social context , and vice versa. One of the main socio-political approaches is Critical Discourse Analysis , which focuses on power structures (for example, the power dynamic between a teacher and a student) and how discourse is influenced by society and culture. Critical Discourse Analysis is born out of Michel Foucault’s early work on power, which focuses on power structures through the analysis of normalized power .

Normalized power is ingrained and relatively allusive. It’s what makes us exist within society (and within the underlying norms of society, as accepted in a specific social context) and do the things that we need to do. Contrasted to this, a more obvious form of power is repressive power , which is power that is actively asserted.

Sounds a bit fluffy? Let’s look at an example.

Consider a situation where a teacher threatens a student with detention if they don’t stop speaking in class. This would be an example of repressive power (i.e. it was actively asserted).

Normalized power, on the other hand, is what makes us not want to talk in class . It’s the subtle clues we’re given from our environment that tell us how to behave, and this form of power is so normal to us that we don’t even realize that our beliefs, desires, and decisions are being shaped by it.

In the view of Critical Discourse Analysis, language is power and, if we want to understand power dynamics and structures in society, we must look to language for answers. In other words, analyzing the use of language can help us understand the social context, especially the power dynamics.

While the above-mentioned approaches are the two most popular approaches to discourse analysis, other forms of analysis exist. For example, ethnography-based discourse analysis and multimodal analysis. Ethnography-based discourse analysis aims to gain an insider understanding of culture , customs, and habits through participant observation (i.e. directly observing participants, rather than focusing on pre-existing texts).

On the other hand, multimodal analysis focuses on a variety of texts that are both verbal and nonverbal (such as a combination of political speeches and written press releases). So, if you’re considering using discourse analysis, familiarize yourself with the various approaches available so that you can make a well-informed decision.

How to “do” discourse analysis

As every study is different, it’s challenging to outline exactly what steps need to be taken to complete your research. However, the following steps can be used as a guideline if you choose to adopt discourse analysis for your research.

Step 1: Decide on your discourse analysis approach

The first step of the process is to decide on which approach you will take in terms. For example, the language in use approach or a socio-political approach such as critical discourse analysis. To do this, you need to consider your research aims, objectives and research questions . Of course, this means that you need to have these components clearly defined. If you’re still a bit uncertain about these, check out our video post covering topic development here.

While discourse analysis can be exploratory (as in, used to find out about a topic that hasn’t really been touched on yet), it is still vital to have a set of clearly defined research questions to guide your analysis. Without these, you may find that you lack direction when you get to your analysis. Since discourse analysis places such a focus on context, it is also vital that your research questions are linked to studying language within context.

Based on your research aims, objectives and research questions, you need to assess which discourse analysis would best suit your needs. Importantly, you  need to adopt an approach that aligns with your study’s purpose . So, think carefully about what you are investigating and what you want to achieve, and then consider the various options available within discourse analysis.

It’s vital to determine your discourse analysis approach from the get-go , so that you don’t waste time randomly analyzing your data without any specific plan.

Step 2: Design your collection method and gather your data

Once you’ve got determined your overarching approach, you can start looking at how to collect your data. Data in discourse analysis is drawn from different forms of “talk” and “text” , which means that it can consist of interviews , ethnographies, discussions, case studies, blog posts.  

The type of data you collect will largely depend on your research questions (and broader research aims and objectives). So, when you’re gathering your data, make sure that you keep in mind the “what”, “who” and “why” of your study, so that you don’t end up with a corpus full of irrelevant data. Discourse analysis can be very time-consuming, so you want to ensure that you’re not wasting time on information that doesn’t directly pertain to your research questions.

When considering potential collection methods, you should also consider the practicalities . What type of data can you access in reality? How many participants do you have access to and how much time do you have available to collect data and make sense of it? These are important factors, as you’ll run into problems if your chosen methods are impractical in light of your constraints.

Once you’ve determined your data collection method, you can get to work with the collection.

Step 3: Investigate the context

A key part of discourse analysis is context and understanding meaning in context. For this reason, it is vital that you thoroughly and systematically investigate the context of your discourse. Make sure that you can answer (at least the majority) of the following questions:

• What is the discourse?
• Why does the discourse exist? What is the purpose and what are the aims of the discourse?
• When did the discourse take place?
• Where did it happen?
• Who participated in the discourse? Who created it and who consumed it?
• What does the discourse say about society in general?
• How is meaning being conveyed in the context of the discourse?

Make sure that you include all aspects of the discourse context in your analysis to eliminate any confounding factors. For example, are there any social, political, or historical reasons as to why the discourse would exist as it does? What other factors could contribute to the existence of the discourse? Discourse can be influenced by many factors, so it is vital that you take as many of them into account as possible.

Once you’ve investigated the context of your data, you’ll have a much better idea of what you’re working with, and you’ll be far more familiar with your content. It’s then time to begin your analysis.

Step 4: Analyze your data

When performing a discourse analysis, you’ll need to look for themes and patterns .  To do this, you’ll start by looking at codes , which are specific topics within your data. You can find more information about the qualitative data coding process here.

Next, you’ll take these codes and identify themes. Themes are patterns of language (such as specific words or sentences) that pop up repeatedly in your data, and that can tell you something about the discourse. For example, if you’re wanting to know about women’s perspectives of living in a certain area, potential themes may be “safety” or “convenience”.

In discourse analysis, it is important to reach what is called data saturation . This refers to when you’ve investigated your topic and analyzed your data to the point where no new information can be found. To achieve this, you need to work your way through your data set multiple times, developing greater depth and insight each time. This can be quite time consuming and even a bit boring at times, but it’s essential.

Once you’ve reached the point of saturation, you should have an almost-complete analysis and you’re ready to move onto the next step – final review.

Step 5: Review your work

Hey, you’re nearly there. Good job! Now it’s time to review your work.

This final step requires you to return to your research questions and compile your answers to them, based on the analysis. Make sure that you can answer your research questions thoroughly, and also substantiate your responses with evidence from your data.

Usually, discourse analysis studies make use of appendices, which are referenced within your thesis or dissertation. This makes it easier for reviewers or markers to jump between your analysis (and findings) and your corpus (your evidence) so that it’s easier for them to assess your work.

When answering your research questions, make you should also revisit your research aims and objectives , and assess your answers against these. This process will help you zoom out a little and give you a bigger picture view. With your newfound insights from the analysis, you may find, for example, that it makes sense to expand the research question set a little to achieve a more comprehensive view of the topic.

Let’s recap…

In this article, we’ve covered quite a bit of ground. The key takeaways are:

• Discourse analysis is a qualitative analysis method used to draw meaning from language in context.
• You should consider using discourse analysis when you wish to analyze the functions and underlying meanings of language in context.
• The two overarching approaches to discourse analysis are language-in-use and socio-political approaches .
• The main steps involved in undertaking discourse analysis are deciding on your analysis approach (based on your research questions), choosing a data collection method, collecting your data, investigating the context of your data, analyzing your data, and reviewing your work.

If you have any questions about discourse analysis, feel free to leave a comment below. If you’d like 1-on-1 help with your analysis, book an initial consultation with a friendly Grad Coach to see how we can help.

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

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30 Comments

This was really helpful to me

I would like to know the importance of discourse analysis analysis to academic writing

In academic writing coherence and cohesion are very important. DA will assist us to decide cohesiveness of the continuum of discourse that are used in it. We can judge it well.

Thank you so much for this piece, can you please direct how I can use Discourse Analysis to investigate politics of ethnicity in a particular society

Fantastically helpful! Could you write on how discourse analysis can be done using computer aided technique? Many thanks

I would like to know if I can use discourse analysis to research on electoral integrity deviation and when election are considered free & fair

I also to know the importance of discourse analysis and it’s purpose and characteristics

Thanks, we are doing discourse analysis as a subject this year and this helped a lot!

Please can you help explain and answer this question? With illustrations,Hymes’ Acronym SPEAKING, as a feature of Discourse Analysis.

What are the three objectives of discourse analysis especially on the topic how people communicate between doctor and patient

Very useful Thank you for your work and information

thank you so much , I wanna know more about discourse analysis tools , such as , latent analysis , active powers analysis, proof paths analysis, image analysis, rhetorical analysis, propositions analysis, and so on, I wish I can get references about it , thanks in advance

Its beyond my expectations. It made me clear everything which I was struggling since last 4 months. 👏 👏 👏 👏

Thank you so much … It is clear and helpful

Thanks for sharing this material. My question is related to the online newspaper articles on COVID -19 pandemic the way this new normal is constructed as a social reality. How discourse analysis is an appropriate approach to examine theese articles?

This very helpful and interesting information

This was incredible! And massively helpful.

I’m seeking further assistance if you don’t mind.

Found it worth consuming!

What are the four types of discourse analysis?

very helpful. And I’d like to know more about Ethnography-based discourse analysis as I’m studying arts and humanities, I’d like to know how can I use it in my study.

Amazing info. Very happy to read this helpful piece of documentation. Thank you.

is discourse analysis can take data from medias like TV, Radio…?

I need to know what is general discourse analysis

Direct to the point, simple and deep explanation. this is helpful indeed.

Thank you so much was really helpful

really impressive

Thank you very much, for the clear explanations and examples.

It is really awesome. Anybody within just in 5 minutes understand this critical topic so easily. Thank you so much.

Thank you for enriching my knowledge on Discourse Analysis . Very helpful thanks again

This was extremely helpful. I feel less anxious now. Thank you so much.

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Discourse analysis, trust and marketing

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In order to understand the service encounter, which lies at the heart of all marketing processes, it is necessary to focus on consumer and consumercontact personnel interactions. We view the marketing encounter between the consumer and organisation personnel as a narrative event. Since social life is a narrative (MacIntyre 1981), what we are saying is that marketing processes are part of the narrative of our social lives. We understand narrative as a discursive ‘form of meaning making’ (Polkinghorne 1988, p. 36). We use Potter and Wetherell’s approach to discourse analysis (1987) to focus less on an objective outcome constructed in the marketing encounter (the transaction, the purchase) and more on the variations and consistencies in language use, to discern what collective, interpersonal meaning is being constructed in the encounter. In other words, we look at what people say and consider how this then creates the marketing encounter. In this chapter we explore this encounter and examine discursive processes for capitalising on and building trust in marketing encounters.

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Halliday, S., Catulli, M. (2013). Discourse analysis, trust and marketing. In: Candlin, C.N., Crichton, J. (eds) Discourses of Trust. Palgrave Studies in Professional and Organizational Discourse. Palgrave Macmillan, London. https://doi.org/10.1007/978-1-137-29556-9_19

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Exploring discourse analysis for making meaningful decisions

Last updated

20 March 2023

Reviewed by

Miroslav Damyanov

Discourse analysis is an interdisciplinary field that studies how conversations are structured and used to create meaning. It examines how language is used in written texts, spoken conversations, and digital media conversations.

The method can be used to identify how participants in a conversation influence it and how their words and phrases shape it.

From everyday conversation to political speeches and media representations, discourse analysis can shed light on how language shapes the world.

You can learn the basics of this wide-ranging field in this article.

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• What is discourse analysis?

This interdisciplinary method relies on the systematic analysis of spoken or written communications, focusing on how language is used to form meaning, convey social identity, and reinforce power relations.

The method is used in several different contexts, ranging from everyday conversations to political speeches and representations in the media.

• What is discourse analysis used for?

Discourse analysis is used whenever researchers want to gain a deeper understanding of the social and cultural contexts that drive language use in a given area.

Some common uses for discourse analysis include the following:

Understanding how language use reflects and reinforces social and cultural norms

Examining how power relations are constructed and maintained through language

Identifying patterns and trends in language use over time and across different contexts

Analyzing how social identities are constructed through language

Investigating how language is used to persuade or influence others

Informing the development of language teaching and learning materials

Supporting policy and decision-making in areas such as media, politics, and education

Understanding how political actors use language to persuade, influence, and mobilize support

Studying how language in media representations constructs social reality and shapes public opinion

Analyzing how legal language is used to construct legal concepts and reinforce power relations

Examining how everyday language is used to negotiate social relationships

• The main approaches to discourse analysis

As an interdisciplinary field, discourse analysis can be approached from radically different perspectives depending on who is performing the analysis and the field they are in.

The broad fields where this method is used are discussed below.

In sociology, discourse analysis is used to study how language is used to construct social reality.

It enables sociologists to examine how language is used to create and maintain social structures, impact social identity, and affect changes to the social order.

One of the key ideas in sociology is that social reality is constructed through the way society uses language. Sociologists believe that language evolves as a reflection of a culture’s existing values and the power hierarchies that have resulted from those values. They argue that the use of language can reinforce those values and structures.

Sociolinguistics

As the study of the relationship between language and society, sociolinguistics can benefit greatly from discourse analysis.

The method allows sociolinguists to examine how language is used in specific social contexts, ranging from conversations the average person has with their neighbor to the speeches a politician broadcasts to millions of listeners.

Sociolinguists believe a variety of social factors inform the language we choose to use. 

Philosophers employ discourse analysis to study how language is used to construct meaning and convey philosophical concepts. It is used in this field to examine how language constructs truth, knowledge, meaning, and social and cultural reality.

Linguistics

Linguists can use discourse analysis to examine how a language’s structure evolves over time and how social and cultural factors impact languages. When linguists understand how these social factors change language, they can draw more informed conclusions.

Artificial intelligence

Natural language processing systems are designed by programmers to help computers understand human language. Discourse analysis is used to study the structure and meaning of language in order to develop algorithms that can analyze and interpret language use. It can also help in the development of chatbots, virtual assistants, and other conversational interfaces.

• Steps to conduct discourse analysis

The steps involved in discourse analysis can vary depending on the specific approach and methodology used. Outlined below is a general guide to the process.

1. Define the research question

The first step is to clearly define what you’ll be researching. Identify the key concepts, themes, or issues you’ll explore as you conduct the analysis.

2. Select a data sample

Next, you need to gather the data sample you’ll be using for the research. This could include written or spoken texts.

Depending on the subject being studied, you may gather interviews, speeches, news articles, social media posts, or other relevant forms of communication.

3. Collect and transcribe the data

Spoken data should be transcribed into written form as accurately as possible. This includes both verbal and non-verbal cues.

If you have collected text data, you can skip this step.

4. Analyze the data

Now it’s time to analyze the data to look for patterns or themes that emerge in the way language is used.

The patterns you look for will depend on the subject you’re performing analysis for. Take careful notes of what you notice for further analysis in the next step.

5. Identify themes and categories

With the data analyzed and patterns notated, it’s time to begin looking for common themes among those patterns. These might be specific linguistic features like word choice, metaphor use, or speaking register. They may also be based on broader themes or topics.

6. Interpret the data

Once you have identified themes and categories, you can begin to interpret the data to develop insights and conclusions about the communication being analyzed. This involves reflecting on the data in relation to the research question, drawing connections between the identified items and your research question, and developing a coherent and nuanced interpretation of the data.

7. Write up your findings

Finally, you can write up your findings, drawing on your analysis and interpretation of the data. Your write-up should clearly present your research question , the methods and data used, the themes and categories identified, and your interpretation of the data.

You should also discuss your findings’ implications and any limitations or challenges you encountered during the process.

• Advantages and disadvantages of discourse analysis

Now you understand what discourse analysis is and the basics of how to perform it, you can start evaluating whether or not it’s the right choice for achieving your research goals.

Below is a list of the advantages and disadvantages of using discourse analysis:

Provides a deeper understanding of communication —the method can help identify factors that influence communication, such as power dynamics, social norms, and cultural values.

Provides insights into social issues —by analyzing communication patterns, researchers can gain insights into social issues such as inequality, discrimination, and exclusion.

Uncovers implicit meaning —researchers can reveal hidden meanings and messages in communication.

Reveals changes over time —researchers can gain insights into how the public views and relates to social issues over time by analyzing historical data.

Informs policy and practice —by revealing the underlying social structures and power relations that shape communication, researchers can identify areas for intervention and develop strategies to address social issues.

Disadvantages

Time-consuming —the process of collecting the large amount of data needed for discourse analysis and then transcribing, analyzing, and interpreting it can be time-intensive.

Highly subjective —different researchers may interpret the same data differently, leading to potential disagreements about findings.

Requires advanced training —researchers need to be familiar with the specific methodological approaches and techniques used in discourse analysis

Limited by data availability —conducting a thorough analysis can be challenging if data related to the subject being studied is limited or unavailable.

Doesn’t generalize well —discourse analysis tends to focus on specific instances of communication and may not produce findings that can be generalized to broader populations or contexts.

Discourse analysis is a powerful and versatile research method that can help researchers study how language use reflects and reinforces social structures and identities.

By using the method, researchers can examine the linguistic features of different types of discourse across social contexts. Through that analysis, they can gain insights into how language use is shaped by complex social factors.

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• Open access
• Published: 03 February 2016

A multimodal discourse analysis of the textual and logical relations in marketing texts written by international undergraduate students

• Hesham Suleiman Alyousef   ORCID: orcid.org/0000-0002-9280-9282 1  

Functional Linguistics volume  3 , Article number:  3 ( 2016 ) Cite this article

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Thematic progression and the composition of information value contribute to the development of well-structured meaningful text. Discourse-based research of the textual features has been confined to language learning and workplace contexts, and in particular advertising and marketing research. However, no published study has explored and analysed the multimodal textual and the logic-semantic features in tertiary marketing texts. This case study employed a Systemic Functional Multimodal Discourse Analysis (SF-MDA) to investigate and compare thematic progression patterns and composition of information value in five business marketing plan reports. It also aimed to investigate the logico–semantic expansions between the visual semiotic resources and the text surrounding them. The SF-MDA of the marketing plan texts is underpinned by Halliday’s (1994) systemic functional linguistics, Kress and van Leeuwen’s (1996) composition of information value and Martinec and Salway’s (2005) system for multimodal discourse analysis of logico–semantic relations. The findings of the SF-MDA revealed the extensive use of Theme reiteration pattern, followed by linear thematic progression pattern. Although multiple-Theme pattern was minimally employed, disciplinary-specific uses of this pattern in marketing discourse emerged. The findings suggest that the students have managed professional workplace practices by showing their understandings of marketing as part of overall business management. A number of other interesting findings related to textual and logico–semantic relations that exist between the tables and the graphs and the accompanying text were revealed. The SF-MDA of informational choices in the marketing texts extends Kress and van Leeuwen’s (1996) functional interpretations of visual artefacts in terms of compositional zones. As the intersemiotic logic-semantic relations between graphs and tables and the orthographic texts surrounding them play a vital role in marketing discourse, tutors can introduce ways of expanding the meaning-making potential in these semiotic resources. Other pedagogical implications for the teaching and learning of writing are presented, particularly in the teaching of English for Business students.

Introduction

Thematic progression and the composition of information value contribute to the development of well-structured meaningful message, thereby providing cohesion within a text. Theme is defined as the “point of departure for the message; it is that which locates and orients the clause within its context” (Halliday and Matthiessen 2014 : 64). Theme identifies what the clause is about, and Rheme is the remaining elements of the message that develop the Theme. For example, ‘ The budget in the sentence “ The budget will increase in each period ” is the Theme and the reminder of the sentence is the Rheme. Students’ awareness of thematic progression patterns helps them produce naturally flowing texts, thereby enhancing their language literacy skills. Academic literacies are construed in the present case study as set of socially situated multimodal literacy practices. Halliday’s ( 1978 , 1994 ) social semiotic approach to language, Systemic Functional Linguistics (hereafter SFL), suits the context of the present study: it views knowledge as the product of ongoing situated social literacy practices, contested around the meaning making processes. SFL sets out the explanation of how humans create meaning of language and various semiotic resources that represent the mode of discourse, a textual feature that will be discussed next.

SFL postulates language as a meaning making semiotic potential that embodies three kinds of language metafunctions: ideational oriented towards the field of discourse and construed by the experiential and the logical meanings, the interpersonal meaning oriented towards the tenor of discourse, and the textual oriented towards the mode of discourse. The textual metafunction weaves the ideational and the interpersonal meanings into a textual whole. Martinec ( 1998 : 162) states that feature selections and structures of the textual meaning “enable the ideational and interpersonal ones to form the cohesive wholes called phases”. Thus, any stretch of written text can be said to be cohesive when it realises the ideational, interpersonal, and textual meanings.

The three language metafunctions provide powerful linguistic research tools for a Systemic Functional Multimodal Discourse Analysis (henceforth SF-MDA) (Alyousef 2013 ; O’Halloran 2008b , 2009 , 2011 ) of texts: TRANSITIVITY (participants, processes, and circumstances) and conjunctions, MOOD (speech function) and modality (obligation and degree of certainty or usuality), and Theme and Information structure and the non-structural system of Cohesion (reference, substitution and ellipsis). Lea and Street ( 2006 : 373) argue that multimodal analysis aids in theorising “the multimodal nature of literacy, and thus of different genres, that students need to master in order to represent different types of curriculum content for different purposes, and therefore to participate in different activities”.

Due to space constraints, however, the SF-MDA aims to investigate and compare the construal of the textual metafunction in two multimodal data sets that comprised three students’ major assignments and a tutor’s two sample texts on a key topic in the Integrated Marketing Topics course, namely a marketing plan. The textual metafunction is construed by thematic progression and the composition of information value in the visual-verbal mode, as they play a major role in the unfolding of multimodal marketing texts. The SF-MDA also aims to investigate the logico–semantic relations between the tables and graphs and the text surrounding them. Garzone ( 2009 : 156) points out that “so far, contributions from linguists specifically dealing with multimodality in business discourse have been relatively few.” As multimodality in business discourse is an increasingly growing field of research, Integrated Marketing Topics course suits the aim of my study since it is one of the foundation courses in the Business of Management (Marketing) undergraduate program. Moreover, insights gained from these analyses may be valuable for English for Specific Purposes (ESP) and English for Business Purposes (EBP) courses. The present study is, to the best of my knowledge, the first of its kind to explore the way international undergraduate business students construct cohesive and logically connected multimodal marketing texts.

Literature review

As the SF-MDA aims to investigate and compare the construal of the textual metafunction and the logico–semantic relations in the multimodal marketing discourse, it is pertinent to provide an overview of Halliday’s ( 1994 ) Theme and Information Structure systems, Kress and van Leeuwen’s ( 1996 ) system for the composition of information value, and Martinec and Salway’s ( 2005 ) system for image-text logico–semantic relations.

Theme and Information Structure are the major structural systems within the textual metafunction in Halliday’s ( 1994 ) SFL approach since they facilitate the development of a meaningful message, thereby providing cohesion within language. Theme involves three major systems: choice of marked or unmarked Theme, choice of predicated or unpredicated Theme, and choice of Theme type.

An unmarked Theme means “the most typical/usual” (Eggins 2007 : 318), while a marked Theme refers to “atypical, unusual” choice whereby the Theme in a declarative clause is something other than subject. A marked Theme is a variation of the unmarked whereby focused information is foregrounded . The unmarked Theme conflates with the MOOD structure constituent- i.e. Subject (in a declarative clause), Finite (in an interrogative), Predicator (in an imperative), or WH (in a WH-interrogative); the marked Theme conflates with adverbial and prepositional group/phrase to provide circumstantial details about an activity, as in: “ in this market plan of Alfa , we will include a financial performance from the beginning up until period 9”. The italicised Theme in this example moved to thematic position. Marked Themes add coherence and emphasis to texts through the use of Theme Predication, which includes thematic and informational choices. Clauses with predicated Themes always have it  +  verb be  +  theme and the non-predicated agnates: e.g. “ It was 2 years ago that he quitted smoking”/“ He quitted smoking 3 years ago”.

There are three different Theme types (Table  1 ): topical, interpersonal and textual. All clauses contain a topical Theme, whereas interpersonal and textual Themes are optional. Topical Themes can be ellipsed in clauses that form a hypotactic relation. A hypotactic relation is set up when a dependent clause is connected to an independent clause by a conjunctive device. For example, the following sentence has two topical themes, “our plant capacity” in the first clause and an ellipsed one in the second, in addition to the textual theme ‘and’: “ Our plant capacity is expected to experience a growth and will require re-assessment and evaluation of our current manufacturing capacity”.

The first thematic progression pattern, Theme reiteration (or constant Theme) pattern, reiterates or maintains the Theme focus rather than developing it. Another thematic pattern is the linear (or ‘sequential’/‘zig-zag’) pattern, in which information placed in Rheme position is packaged in a subsequent Theme, as illustrated in Fig.  1 .

Linear (or ‘sequential’/‘zig-zag’) Theme pattern

The cumulative development of Theme in this pattern makes a text cohesive through the use of newly introduced ideas. The theme in a subsequent clause is picked up from the Rheme of the previous one. A third form of thematic progression is referred to as the multiple-Theme (or fan) pattern or split Rheme progression pattern (Fig.  2 ).

Multiple-Theme or split Rheme progression pattern

A Rheme may involve a number of different pieces of information, each of which may be picked up and used as the Themes in subsequent clauses. Theme/Rheme conflates with the information focus functions of Given/New.

The system of Information Structure consists of two functional elements, Given (or Known) and New, that are marked off in speech by tone or a pitch contour. New information is typically marked by tonic prominence since it refers to “what is new or unpredictable” and, therefore, carries the information focus; Given information precedes New information, and it refers to “what is already known or predictable” (Halliday and Matthiessen 2014 : 89). Given information is shared by the reader/writer or speaker/hearer. As the present study is concerned with written texts, the phonological indices of the Information Structure system were not investigated in the present study; instead, Kress and van Leeuwen’s ( 1996 ) system of the composition of information value is employed in the analysis of the textual organization in tables and graphs.

In his book The Language of Displayed Art , O’Toole ( 1994 ) was the first to utilise SFL in multimodal discourse analysis (MDA). Kress and van Leeuwen ( 1996 ) were the first to outline methods for the analysis of the textual layout in images by proposing three main systems of meaning-making potential: composition, framing and salience. The first system is achieved through the principle of information value compositional zone layout (Fig.  3 ), which is presented in terms of zones: Centred vs. Polarised, Circular, Mediator composition, horizontal (or left-right) Given-New and vertical (or up-down) Ideal-Real compositions (or dimensions).

The grammar of visual artefacts in terms of compositional zones (Kress and van Leeuwen 1996 )

A Centred composition is perceived by some element(s) appearing in the centre, whereas a Circular refers to a composition which includes non-central elements that are spatially spread around the centre. A Mediator composition forms a bridge between dissimilar non-central elements. The second system, framing, is expressed through visual framing, whereas the salience system is realised through salience features. The semiotic potential of visual framing is the separation of elements by frame-lines, pictorial framing devices, empty spaces, and so on. Finally, salience attracts a reader’s attention through the semiotic resources of position, size, tonal value or colour, sharpness, and so on (van Leeuwen 2005a ). Bateman ( 2011 : 52) presses the need for “more empirically grounded analysis of a broader range of multimodal documents” in order to verify or disprove Kress and van Leeuwen’s interpretations of the composition of information value. Following Bateman’s ( 2011 : 52) claim, it is essential to investigate Kress and van Leeuwen’s functional interpretation of Given-New/ Ideal-Real to find out if these ‘technical labels’ are capable of bringing “a concrete, readily verbalised meaning to the interpretation” of the marketing multimodal texts.

The SF-MDA of the composition of information value in terms of Given-New and Ideal-Real lends itself to the investigation of the logico-semantic image-text relations that construe these artefacts. Martinec and Salway ( 2005 : 339) state, systemic functional semiotics is “the one theoretical framework whose followers have concerned themselves with [intersemiotic] relations between images and texts”. Martinec and Salway ( 2005 ) system for image–text logico–semantic relations is based on Halliday and Hasan’s ( 1976 ) three main sub-types of expansion in texts: elaboration, in the case when a mode (image) clarified the other (text), extension, if images added information to texts, and enhancement, if images prompted information such as how, when, where, or why the text was taking place. In elaboration relation, the same participants, processes and circumstances are depicted and referred to. In extension, images add new but related information is referred to or depicted. Finally, in enhancement relation, related temporal, spatial or causal information is provided. What follows is a review of the literature which takes SFL and multimodal communication and representation into account.

Discourse-based research of the textual features has been confined to language learning (Ebrahimi and Ebrahimi 2012 ; Jalilifar 2010 ; Medve and Takač 2013 ; Mellos 2011 ) and workplace (Bargiela-Chiappini 2009 ; Camiciottoli 2010 ; Clatworthy and Jones 2001 ; Fitchett and Caruana 2015 ; Forey 2002 ; Thomas 1997 ) contexts, and in particular advertising and marketing research (Ardley and Quinn 2014 ; Copley 2010 ; Kim et al. 2014 ; Oakes and Oakes 2012 ). Fitchett and Caruana ( 2015 ), for example, reviewed the development of studies in marketing and consumer research. Thomas ( 1997 ) investigated thematic progression in a series of management messages in the annual reports of a company. The results highlighted significant decrease in the use of the personal pronoun ‘we’ from 1984 to 1988, along with a corresponding increase in the use of inanimate nominal groups as themes. Camiciottoli ( 2010 ) investigated discourse conjunctive devices in financial disclosure texts. The findings indicated that the pragmatic use of disclosure influences the interpretation of the message. Similarly, Forey ( 2002 ) investigated the function performed by Theme in workplace texts, which included 30 memos, 22 letters and 10 reports. Marked Theme played a crucial role in representing the workplace as a depersonalised, material world. The interpersonal Theme was realised by similar features across the three types of texts. Clatworthy and Jones ( 2001 ) investigated the effect of thematic structure on the extent of readability variability in 60 chairman’s statements. The findings showed that the introduction was systematically easier to read than other parts of the statement, contradicting prior objective research on accounting narratives. The results indicated that the thematic structure in the statement was a key driver of the variability of annual report readability.

Some studies conducted discourse analysis and interviews to identify key themes in marketing workplace discourse. For example, Ardley and Quinn ( 2014 ) examined the perceptions of senior marketers in regards to their approaches to the development and implementation of marketing plans. The findings suggest that senior marketers written plans function as cues and guides, rather than prescriptive actions which stifle creativity and innovation. A diverse breadth of language and ways of enacting contextual tasks and accomplishing goals is what characterises marketing activities. This view contrasts with Lee’s ( 2005 ) and Oakes and Oakes ( 2012 ) view that the sequential steps in market planning model create a sense of order. Along similar lines, Copley ( 2010 ) conducted a discourse analyses of 14 interview exchanges to investigate the ways in which marketing is seen and conducted in Sales and Marketing Executives (SMEs) by SME principals and support agency practitioners in England. The findings identified key themes, which indicate the need to include critical marketing issues when considering the nature of SME marketing, which challenges accepted notions of orthodox and relational SME marketing. Oakes and Oakes ( 2012 ) argue that the rhetorical use of verbal and visual metaphor to enhance legitimacy in accounting and marketing suggest a strong link between them.

Whereas multimodal communication research in tertiary contexts has been confined to mathematics (de Oliveira and Cheng 2011 ; Guo 2004 ; O’Halloran 1996 , 2000 , 2004 , 2005 , 2008a , 2009 ), history (North 2005 ), science and computing (AlHuthali 2007 ; Alshammari 2011 ; Drury et al. 2006 ; Hsu and Yang 2007 ; Jones 2006 ), journalism and media (Hawes 2015 ), and nursing (Okawa 2008 ), SFL-based investigations of tertiary business discourse were limited to a few studies (Alyousef 2013 , 2015a , 2015b ; Alyousef and Alnasser 2015a , b ; Alyousef and Mickan in press ). Hawes ( 2015 ) for example, investigated and compared thematic progression in professional journalists’ texts with those of comparable length written by 18 international students in a pre-MA course, Inter-Communication. The findings suggest teaching the principles of thematic progression, particularly to non-native speakers of English. Okawa ( 2008 ) investigated the process of constituting academic literacy practices of a Japanese first year nursing student. She employed SFL in the analysis of texts to investigate, respectively, discourse at the epistemological level and texts at the lexico-grammatical level. The findings showed that discipline-specific knowledge is acquired through socialisation into a particular discipline. Whereas Alyousef ( 2013 ) examined the experiential meanings within the multimodal finance texts, Alyousef and Mickan ( in press ) investigated the ideational meanings in management accounting texts. Along similar lines, Alyousef and Alnasser ( 2015a , b ) investigated the use of cohesive devices in a tertiary finance and management accounting texts. The findings revealed that lexical cohesion is the most common resource for cohesion in the two Business texts, and in particular repetition of the same lexical items, followed by reference. Theme reiteration is used to define the numerical values in the tables. Alyousef ( 2015 a) employed an SF-MDA of Theme and the composition of information value in tertiary finance texts that encompassed tables and graphs. The findings showed the high frequency of Theme reiteration pattern, the rare occurrence of linear Theme pattern, and the minimal use of multiple-Theme pattern. In a similar way, Alyousef’s ( 2015 b) investigation of management accounting texts revealed the frequency of Theme reiteration and the linear pattern. The present study aims to contribute to this line of research by investigating a key topic in tertiary multimodal marketing texts.

Having presented an overview of the literature relevant to the present study, next I describe the data and method of analysis.

Data and method of analysis

The corpus is composed of three students’ major assignments (13,664 words) and a tutor’s two sample texts (6949 words) written in English on a key topic in the Integrated Marketing Topics course, namely a marketing plan. The students were enrolled in the Business of Management (Marketing) undergraduate program, and they were given the pseudonyms Nura, Hind, and Zohoy. The five texts were comparable since the main topic underlying the tasks was similar.

The SF-MDA of the two data sets is based on the theoretical tools of Halliday and Matthiessen’s ( 2014 ) Theme system and Kress and van Leeuwen’s ( 1996 ) system of the composition of information value. As marketing texts are multimodal, I employed Martinec and Salway’s ( 2005 ) system for the investigation of image-text intrasemiotic (within a visual semiotic mode, a table/graph) and intersemiotic (across a visual semiotic mode and the text surrounding it) logico–semantic relations. These tools seem to be suitable for the purpose of this study because they reveal the textual and the logical configurations made at the intersection of tables and graphs and the accompanying texts.

Following Halliday and Matthiessen ( 2014 ), independent clauses in tables and graphs were numbered and annotated in order to calculate the frequency of occurrence of each Theme type across the two data sets. I utilised the students’ intuitive understandings or the intended reading paths (van Leeuwen 2005b ) of the graphs and tables in order to transcribe and annotate the frequency and the nature of Theme patterns and the composition of information value. Ellipsed experiential Themes were included in the SF-MDA. Instances of implicit Theme patterns in the tables and graphs were italicised and placed in square brackets, whereas implicit finites in Rheme position were placed in square brackets. Numerical values in the tables were annotated as New if they were not provided in the assignment task sheet.

Consideration is given to validity and reliability, which are crucial features of all research. Reliability was achieved through iterative cross-checking of the analyses, followed by member checking agreement to verify the annotations of thematic patterns. As for validity, I calculated the percentage for the frequency of occurrence of each Theme pattern per the total instances of Theme patterns in a text. This was calculated by dividing the sub-total number of occurrences of each pattern by the total number of occurrences of the overall Theme patterns and then multiplying this number by 100. The percentage total adds up to 100 %, equivalent to the total number of Themes. The use of numerical/quantitative data in this study aims to make statements such as “higher,” “fewer,” and “most” more precise.

What follows is the findings and the discussion of the SF-MDA of marketing texts.

Results and discussion

This section presents and discusses the findings of the SF-MDA of market planning texts, including an overview of the context of the study.

An overview of context

Students were required to engage in workplace practices by developing a business marketing plan report to show their understanding of marketing, their ability to comprehensively analyse their environment, and their creative marketing oriented solutions and written communications. The terms marketing plan and market planning (and more generally business planning) are used interchangeably to refer to “a technology, a set of techniques and activities, that assists an organization in achieving an appropriate alignment of external environment and internal capabilities in order to achieve a desired outcome” (Pulendran et al. 2003 : 478). So businesses need a marketing plan report since it details the analysis, ideas, and plans, linked to what one wants to do with the company. A marketing plan report also communicates the substance of the marketing effort (and the professionalism of its author) to other areas of the organization.

Whereas Nura achieved the highest mark, 81 out of 100, Hind and Zohoy’s marks were 72 and 75 respectively. The word limit for this individual major assignment is 3000 words. This assignment is allotted 40 % of the total mark for the course. Table  2 outlines the key statistics of the three students’ texts and the tutor’s two sample texts. This includes word count, and the number of tables and graphs:

All the four participants used tables and graphs in the analyses of their products and to assist them in making appropriate decisions. Nura and Zohoy’s texts far exceeded the other texts in terms of the number of words, whereas Nura used only two tables compared to the other texts. Nura preferred to include most of her tables in the appendices, while presenting and discussing her findings in the text. This may explain the reason for exceeding the required number of words by 80 %. The five texts encompassed 37 tables and 11 graphs. The total number of tables and graphs in the two data sets was almost the same. These semiotic visual modes achieve a number of functions, as presented in the SF-MDA.

SF-MDA findings and discussion

Table  3 shows thematic progression frequencies for each pattern and the percentages equivalent to the total number of thematic units. It compares the use of thematic progression patterns in the students’ texts and the tutor’s two sample marketing plans, both in the orthographic texts and the tables and graphs. The SF-MDA of thematic progression patterns in the five marketing plan texts revealed the extensive use of Theme reiteration pattern in the two data sets, followed by linear pattern. Multiple-Theme pattern was minimally used in the two data sets.

The SF-MDA showed that whereas Theme reiteration mostly occurred in the students’ tables and graphs (55.80 %), its occurrence in the tutor’s orthographic texts (46.45 %) was higher. This may be mainly ascribed to the fact that most of the numerical values in the tutor’s tables were absent. As these semiotic resources were presented to the students as a sample, it is natural to leave the value cells blank. The aim of the tutor’s two sample texts is to present to the students the rhetorical structure of a marketing plan and what is expected from them to write in each section. As a result, the tutor’s total word count in the tables and the graphs was 65 % below the students (Table  2 ). This may perhaps explain the significant difference between the students’ texts and the tutor’s in terms of the use of theme reiteration. Overall, Theme reiteration comprised over 72 % of thematic progression patterns in the two data sets (Table  3 ). This finding is in line with a number of studies (Alyousef 2015 a, b ; Ebrahimi and Ebrahimi 2012 ; Li and Fan 2008 ) Examples of Theme reiteration pattern are shown in Table  4 (reiterated experiential Themes are italicised).

Instead of repeating the clause “Alex price strategy” in the following one, Nura writes “the other strategy”, using the reference word “other” in order to link this clause with the previous one, thereby making her text more cohesive. Hind employs the topical Themes ‘Amazing Car’ and ‘company’ interchangeably to refer to the same entity. All the participants used inanimate nominal groups as topical themes. This finding is in line with a number of studies (Alyousef 2013 ; Alyousef and Mickan in press ; Iedema 2000 ; Thomas 1997 ). Nura and Zohoy used bullet points to list down, respectively, the marketing and product objectives for Alec and customer groups, thereby making Theme reiterations and other elements implicit, as shown below (implicit Themes are italicised and placed in square brackets; implicit finites in Rheme position are placed in square brackets).

The marketing and product objectives for Alec next 4 years (Th) are: (Rh)

[ The first objective ] [is] Continuing to focus on consumer research.

[ The second objective ] [is] Aim to increase market share …

[ The third objective ] [is] Increase Alec technology capability …

[ The fourth objective ] [is] Increase net margins …

[ The fifth objective ] [is] Increase contribution margin …

[ The sixth objective ] [is] To achieve 72 % brand awareness in the economy market …

[ The last objective ] [is] Increase inventory days … (Nura’s text)

Currently (Text Th), Efficient Motors vehicles (Th) are being purchased by many customer groups (Rh); these (Th) predominately include (Rh):

[ The first customer group ] [are] Families (2F) and high income earners (4F) …

[ The second customer group ] [are] Singles (3U) and enterprisers (5U) …

[ The last customer group ] [are] Singles (3T) and value seekers (1T) … (Zohoy’s text)

The topical Theme “marketing and product objectives for Alec” is implicitly reiterated seven times to draw readers’ attention to focal points. Bullet points grammatically truncate (or encode) ensuing Theme reiterations and the relational identifying or attributive clauses, which link the Rheme with the Theme through the use of verb be . This finding is in line with Nathan’s ( 2013 ) genre-based study of a corpus of 53 marketing and marketing management case reports written by native and non-native postgraduate students at a UK university. These tools could make recall easier and, in turn, “facilitate the transition from prescription to action” (Chiapello and Fairclough 2002 : 198). Although Hind used bullet points in this pattern, she did not employ structural condensation to encode meanings in the most economical manner.

However, there are many different points also risk to competitors.

Financial position

The Amazing Company has a greatest research and development expend…

The Amazing Company High sales value which is 24,236 (mill.) …

Dealer and largest network

The Amazing Company has lowest firm preference percentage …

The Amazing Company has highest number of contribution dealer, …

Vehicle Class

The Amazing Company is having a good market share value …

Hind did not avail from the powerful means of bullet points, as she preferred to reiterate the topical Theme “The Amazing Company” to provide additional information, rather than focusing on the different pieces of information that are related to the company- i.e. financial position, dealer and largest network, and vehicle class. Zohoy used bullet points to present the objectives of his marketing plan, in addition to the implementation plan for his company Efficient Motor. The tutor used bullet points and numbered lists in Text 1 to present his marketing plan goals. The findings of the SF-MDA revealed instances of imperatives in the section entitled “Corporate objectives and goals”, which are typically treated as themes. The imperative is the only type of clause in which the Predicator (the verb) is regularly found as unmarked theme (instances of Theme reiteration are italicised).

Increase the sales/deals from $54.6 to $60 by period 8 in the north, east, west and south. Increase budget for advertising from $210 million to $400 million and promotion from $100 million to $200 million by period 9. (Hind’s Text)

Increase overall dealer ratings 7 to 75 % by period 8.

Increase firm preference by 4.1 to 22 % by period 9.

Increase MSRP from $20,199 to $20,899.

Increase $5 million in advertising (from $80 million to $85 million). (Zohoy’s Text)

Financial Goals

Obtain financing to expand manufacturing capabilities, increase distribution, and introduce two new product lines.

Increase revenues by at least 50 % each year.

Donate at least $25,000 a year to conservation organizations. (Tutor’s Text 1)

Nonfinancial goals

Introduce two new product lines—customized logo clothing …

Enter new geographic markets, …

Develop a successful Internet site, …

Develop its own conservation program … (Tutor’s Text 1)

The tutor used diversified commands, such as “ create a newsletter to go out monthly to customers”, “ offer business card magnets to real estate agents”, and “ add a survey to the website”, which in turn minimizes theme iteration instances. In addition, the tutor minimally employed imperative clauses in Text 2.

All the two data sets included textual Themes that expand a proposition, conjunctions that link two clauses through paratactic (equal status) relations or subordinate two clauses through hypotactic (unequal status) interdependency nexus. A paratactic relation is set up when two or more independent clauses are connected by conjunctive linking devices (such as and, or, either, neither, but, yet, so, then), while a hypotactic relation is set up when a dependent clause is connected to an independent (dominant) clause by a conjunctive binding device (such as when, while, before, after, until, because, if, although, unless). These two types of relations are illustrated below (topical Themes are italicised, implicit topical Themes are italicised and placed in square brackets, linking devices are underlined, and binding devices are in bold):

The total sales (Th) were $39,547,000 in the last 5 years, and our current market share (Th) is 64.3 % (Rh). (Nura’s Text)

The economy situation in the next years (Th) shows there is growth in the industry expected and which (Th) will provide good environment for vehicle sales (Rh). (Nura’s Text)

However , dealer discount (Th) will increase from 12 to 14 % by the end of period 9 as we (Th) believe (Rh) the increase in discount (Th) will increase dealer rating (Rh). (Zohoy’s Text)

We (Th) are not going to increase too much on advertising budget (Rh) in order [ for us ] (Th) to be profitable in 1T market (Rh). (Zohoy’s Text)

They might (Th) not be experts at the sports (Rh) they (Th) engage in (Rh), but they (Th) enjoy themselves outdoors (Rh). (Tutor’s Text 1)

In just three years , (Th) Blue Sky has built some impressive strengths (Rh) while [ Blue Sky ] (Th) looking forward to new opportunities (Rh). (Tutor’s Text 1)

Currently, they (Th) are offering bathroom renovations (Rh), but they (Th) plan on extending into kitchen renovations and extensions as well (Rh). (Tutor’s Text 2)

West Homes (Th) is too far away to threaten Canterbury Renovations’ projected customer base (Rh), but [ they ] (Th) need to be monitored in case they expand eastwards (Rh). (Tutor’s Text 2)

Writers use conjunctions in writing to link clauses and to signpost the way for their readers. Conjunctions tie a message to the immediate context of the preceding clause. They are, therefore, crucial for expressing the logical relations between the clauses. For example, the conjunctive devices in examples 1–8 develop on the meaning of another preceding clause in terms of cause (‘in order to’, and ‘as’), manner (‘while’), addition (‘and’), and variation (‘but’). The second topical theme ‘for us’ in Zohoy’s second example is inserted between square brackets as it is ellipsed and was recovered from the first one. Anaphoric ellipsed topical Themes occur in clauses that form a hypotactic relation. The subject of the second clause is implicit and it is recovered from the first sentence. The thematic complement in the tutor’s text (sentence 6) is marked because the topical theme is not subject, a prepositional phrase functioning as an adjunct: “ In just 3 years , Blue Sky has built some impressive strengths”. It provides orientation or a contextual frame (Davies 1997 ) for the message to follow. The marked Theme conflated with the prepositional phrase in a declarative clause to provide circumstantial details about time. As Halliday and Matthiessen ( 2014 ) argue, marked Themes have the potentiality of being subjects since they are nominals but have not been selected subjects; yet they are thematic since they are foregrounded as the Theme. The second topical theme ‘Blue Sky’ in the tutor’s text is ellipsed.

Linear (or zig-zag) and multiple-Theme patterns were confined to the written texts. The use of the former pattern was higher in the tutor’s text than in the students, 37.42 and 22.87 % respectively. Overall linear Theme pattern was the second most highly occurring pattern in the two data sets (>22 %), compared with multiple-Theme pattern (<8 %). The high use of this pattern contrasts with Alyousef’s ( 2015a , 2015 b) studies, <0.60 and <8.50 % respectively. Multiple-Theme pattern was used by the participants to explain and provide further details related to the market plan. The tutor’s text in the present study more often included instances of this pattern than did the students, 1.49 and 7.74 % respectively. This highlights the importance of this pattern in marketing plan texts. Although the rare occurrence of multiple-Theme pattern in the students texts corresponds with the results in Alyousef’s ( 2015 a) study of finance texts (<2.50 %), it contrasts with Alyousef’s ( 2015 b) study of management accounting texts which lacked the occurrence of this pattern. All the two data sets employed non-defining relative clauses with the pronouns ‘which’, ‘who’, ‘that’ ‘more’ and ‘this’ to give more information about a proposition (a thing) or a person in the previous clause. These elements serve two functions: as a marker of some special status of the clause (i.e. textual) and as an element in the experiential structure (i.e. topical) (Alyousef 2015 a). Examples of linear Theme pattern are shown in Table  5 .

The tutor employs a non-defining relative clause with the pronoun ‘more’ to provide information related to the proposition of adding new logos and slogans. Such clause types are typically separated from the rest of the sentence by commas, semicolons, or parentheses. The clause “At the beginning …” is a non-finite hypotactic enhancing clause acting as a Circumstantial Adjunct.

The use of multiple-Theme pattern by Nura and the tutor (Text 1) was almost the same, 3.32 and 3.34 % respectively. The use of this pattern by Hind and Zohoy was 1 % or below. It is not surprising to find Nura employing these cohesive resources as she had received the highest mark. The use of multiple-Theme pattern in Nura text is shown below (information derived from Rheme is underlined, Themes are in italics).

Alec has some problems that need to be taken into account in making decisions. One of these is the need to keep our high market share and stay leader in the 2E market. In addition, low capacity production requires consideration. (Nura’s Text)

The reason behind our high performance in the economy market is that the vehicle satisfies 2E needs better than the competitor in terms of bigger size vehicle, higher performance horsepower (HP), and high safety . Our safety exceeds competitor by 1 and the quality is the same. Alec is better in safety and the vehicle size is larger and the performance HP is higher. (Nura’s Text)

The main target markets for Alec are 1E and 2E . In 2E market , Alec is doing well in the market. … 1E is −5 % and 2E demand is 0 %, …. Moreover, 2E is the best market for Alec to stay in the future, …. (Nura’s Text)

I decided to focus on advertising and promotion in order to enhance salience and generate awareness. Another reason for my focus on advertising is to promote the new product development and positive image of Alec. Promotions increased from $30 to $35 million. (Nura’s Text)

There are two distinctive assets of Alec which help consumer easily identify offering and build brand salience. Finally, safety attribute are higher than the competitor. … Secondly, bigger size vehicle and high HP than competitor. (Nura’s Text)

The prepositional phrase “ In 2E market ” in Nura’s text (Sentence 3 above) is a marked Theme, and it provides a contextual frame. Eggins (ibid: 320) argues that “skillful writers and speakers choose marked Themes to add coherence and emphasis to their text” through the use of Theme Predication, which includes thematic and informational choices. The tutor used multiple-Theme pattern in order to describe the qualifications of Blue Sky Clothing’s entrepreneurs, Lucy Neuman and Nick Russell, and their experiences (Excerpt 1). He also used this pattern to discuss the reasons underlying his positive outlook for the industry in general and Blue Sky in particular (Excerpt 2), and to present the key features of customized clothing items, which Blue Sky intends to introduce over the next 5 years (Excerpts 3–4).

Blue Sky Clothing was founded 3 years ago by entrepreneurs Lucy Neuman and Nick Russell , Neuman has an undergraduate degree in marketing and worked for several years in the retail clothing industry. Russell operated an adventure business called Go West!, which arranges group trips to locations in Wyoming, Montana, and Idaho, before selling the enterprise to a partner. Neuman and Russell , who have been friends since college, decided to develop and market a line of clothing with a unique—yet universal—appeal to outdoor enthusiasts. (Tutor’s text 1)

The outlook for the industry in general—and Blue Sky in particular—is positive for several reasons . First, consumers are participating in and investing in recreational activities that are near their homes. Second, consumers are looking for ways to enjoy their leisure time with friends and family without overspending. Third, consumers are gaining more confidence in the economy and are willing and able to spend more. (Tutor’s text 1)

While all of the companies listed earlier can be considered competitors, none offers the kind of trendy , yet practical products provided by Blue Sky —and none carries the customized logos and slogans that Blue Sky plans to offer in the near future . In addition, most of these competitors sell performance apparel in high-tech manufactured fabrics. With the exception of the fleece vests and jackets, Blue Sky’s clothing is made of strictly the highest quality cotton, so it may be worn both on the hiking trail and around town. Finally, Blue Sky products are offered at moderate prices, making them affordable in multiple quantities. For instance, a Blue Sky T-shirt sells for $15.99, compared with a competing high-performance T-shirt that sells for $29.99. Consumers can easily replace a set of shirts from one season to the next, picking up the newest colors, without having to think about the purchase. (Tutor’s text 1)

Over the next 5 years, Blue Sky plans to expand the product line to include customized clothing items . Customers may select a logo that represents their sport—say rock climbing. Then they can add a slogan to match the logo, such as “Get over It.” A baseball cap with a bicyclist might bear the slogan, “Take a Spin.” (Tutor’s text 1)

The tutor used the temporal conjunctive adjuncts (‘first’, ‘second’, and ‘third’) to expand (or enhance) the meaning in a preceding clause in terms of time. The tutor also employed multiple-Theme pattern in Text 2 ( Appendix ) in order to list down, in bullet points, the assumptions through which the plan was based on, the objectives, and the recommendations, which included strengths, weaknesses, opportunities, and threats (SWOT) of Canterbury Renovations Company. This pattern was also used to list key issues from the SWOT analysis and the main findings of competitor analysis. Canterbury Renovations is employed as the topical Theme in four instances ( Appendix ) to mention aspects related to marketing strengths, improvements, ways to overcome threats, and the main competitors.

Canterbury Renovations (Th) have a number of marketing strengths (Rh):

[The first strength] [is] technical competence of the proprietors

[The second strength] [is] dedication of the staff

[The third strength] [is] total agreement between proprietors on their objectives

[The fourth strength] [is] financial resources

[The fifth strength] [is] good network of contacts for potential clients, suppliers and tradespersons

[The sixth strength] [is] ability to respond to the needs of the market

[The last strength] [is that] business is located within the target market. (Tutor’s text 2)

The use of bullet points in multiple-Theme pattern grammatically truncate the ensuing Themes and the implicit relational identifying or attributive clauses, which link the Rheme with the Theme through the use of some form of verb be, such as “[The first point] [is the] lack of management skills” ( Appendix , Excerpt 2). The function of the dot points is to avoid repetition of the same or very similar Themes. Second, the bullet points allow for all listed key features of an aspect to be understood as Thematic, so each one is foregrounded in Theme position. If we write the implicit Themes in full then each of these bullet points are backgrounded (or moved to Rheme position). Finally, the tutor extensively employed bullet points to encode structural information and relational identifying processes in the most economical manner. In other words, focusing only on key features of an aspect “while dispensing with peripheral information where possible” (O’Halloran 1999 : 10). Baldry and Thibault ( 2006 : 19) attributed this to the “meaning-compression principle”, which refers to “the effect of the interaction of smaller-scale semiotic resources on higher-scalar levels where meaning is observed and interpreted”. Although multiple-Theme pattern was minimally used in the two data sets, the tutor’s text more often included instances of this pattern than did the students, 7.74 and 1.49 % respectively. This indicates that the use of this pattern is one of the key linguistic features of marketing plan texts. Multiple-Theme pattern is the most difficult one for academic writing students, as they need pack or list a number of different pieces of information in Rheme position, each of which are then picked up and used as the Themes in subsequent clauses. Hind and Zohoy’s minimal use of this pattern in the present study may indicate their limited knowledge of these cohesive resources and probably their limited writing opportunities. These factors, however, did not seem to have hindered their lexico-grammatical choices and the multimodal meaning-making processes in their assignments, as shown below from their use of this pattern and the good results they have achieved in this assignment.

High-technology has two advantages , one is enhancing our capacities; strength is reducing some costs, including labor and material costs. (Hind’s Text)

The Table  2 is defining the different ≤ sic ≥ between Alfa and Defy cars which are both family type car in different company on the market. Defy is the best car for the 2F customer … Alfa is the second highest vehicle in the 2F customer, … (Hind’s Text)

Two main types of market segment purchase Estruck. They are 1T (Value Seekers) and 3T (Singles) . However, 1T segment occupied most of unit of sales, which was 59 % in period 4 … The 3T segment is a niche market as we only had 8 % unit share … (Zohoy’s Text)

Because Estruck only have two types of customers: 1T (Value Seekers) and 3T (Singles) , we consider focus on the main customers … The Value Seekers Segment is a large market with 520,000 unit sales … On the other hand, the Single segment has a smaller market with 377,000 units of sales … (Zohoy’s Text)

The Rheme in the second excerpt “The Table  2 is defining…” in Hind’s text introduced two family car types (‘Alfa’and ‘Defy’), each of which was made Theme in subsequent clauses. Similarly, the two Themes “1T segment” and “the 3T segment” in Zohoy’s text were created from the Rheme in the preceding clause: 1T (Value Seekers) and 3T (Singles). Students’ language proficiency and their previous academic experiences seemed to have facilitated their use of linear and multiple-Theme patterns (Jalilifar 2010 ).

The findings of the SF-MDA also revealed that all the participants employed anticipatory ‘it’ in Subject position with ( be to +) infinitive to give their viewpoints or suggest certain attitude regarding the marketing plan, while remaining in the background through the use of projecting clauses. Projecting clauses are treated as interpersonal Themes since they “express a comment on a proposition” or “constitute the proposition itself” (North 2005 : 439). Some examples of thematised comment from the corpus are given in Table  6 .

The function of projection in the marketing plan texts is to present viewpoints (“it is expected that the increase in profits and market share will continue for the next 4 years.”) and to suggest attitudes (“it is important to focus on corporate advertising to maintain and then increase our preferences”). The comment adjuncts ‘predicted’, ‘required’, ‘important’, ‘easy’, ‘just’, and “expected” express comment, and are in Rheme position since they are part of the verbal groups. This finding contrasts with Hyland’s ( 2005 : 14) claim that since academic assessment genres are “influenced by the dominant ideologies of the genre they are employing”, they lack the writer-reader equality found in peer-oriented research papers. The participants’ use of grammatical metaphors in it-clauses with extraposed subjects is in line with Hewings and Hewings’ ( 2002 ) findings of similar structures in business studies research articles and students’ essays. What follows is the SF-MDA of the tables and the graphs.

The SF-MDA of marketing plan tables and graphs and the accompanying text aim to unpack the elements and the processes (Monteiro and Ainley 2006 ) through which students constructed knowledge of Theme, Given-New/Ideal-Real compositions of information, and the logico-semantic relations that exist between these multisemiotic resources. Figure  4 includes four instances of Theme reiteration pattern in the graph, as the Theme “revenues” in the clause underlying the interpretation of the first bar is taken as the Theme of the ensuing ones, thereby constituting an implicit relational identifying clauses expressed by some form of the verb be that links the Rheme with the Theme. For example, the first bar can be interpreted as “ Revenues for the period 1 [were] $8000 million”. The Theme ‘revenues’ is repeated four times in the interpretation of periods 2–5.

Nura’s 5 years revenues graph

The Rheme conflates with the Given information instead of New, since the revenues represent known information. The 5 bars function intrasemiotically (within the graph) to make meaning. Unlike orthographic texts, the reading path of this graph proceeds from right to left, rather than the opposite. The values in the vertical axis represent Given information since they were stated in the task sheet. In addition, the numerical values that correspond with each period along the horizontal axis do not represent New information. The graph does not only function intrasemiotically but also intersemiotically through the interaction of the graph and the accompanying text, as it prompted Nura in drawing conclusions in the orthographic text. In other words, New information was inferred from the graph: e.g. in period 4 and 5 “revenue increased which is a good predictor that Alec is performing well due to the changes and actions that were taken in periods 4 and 5”. Nura expresses her authorial interpersonal stance, arguing that the increase is ‘a good predictor’. The graph-text logico intersemiotic semantic relation is that of enhancement since it aided Nura in arriving at New related information that is qualified circumstantially by the propositional clause: “due to the changes and actions that were taken in periods 4 and 5”. This clause provides reason (or purpose) for Nura’s viewpoint. Image-text enhancement relation provides related temporal (when, how), spatial (where) or causal (Why) information. Liu & O’Halloran ( 2009 ) argue that image–text relations are metafunctionally integrated across experiential, textual and logical meanings at the discourse stratum.

Similarly, the percentage values in Zohoy’s graph (Fig.  5 ) do not represent New information, as they were stated in the task sheet. Besides, the reading path of this graph proceeds from right to left. The data in the graph aided Zohoy not only in describing the market share of his truck company Estrruck and the competitor Detonka during the past 5 periods, but also in spotting trends and providing interpretive analytical analyses in the accompanying text that assist in arriving at a conclusion. This conclusion represents New information that was inferred from the graph (“Hence, we need to increase establishing dealers in these regions to improve our sales and enhance the dealer relationship”). As O’Halloran ( 1999 : 27) states, “verbal discourse functions to describe commonsense reality, visual display connects our physiological perceptions to this reality and in combination with metaphorical shifts, creates new entities which are intuitively accessible.” This finding exemplifies one of the three ideational complementarity relations, augmentation , mentioned by Unsworth ( 2006 ) and Daly and Unsworth ( 2011 ), where each of the semiotic modes (image/text) provides ideational content that is additional to and consistent with those provided in the other. The other two relations are distribution , where the two modes jointly construct similar content, and divergence , where the ideational content is opposed in the two.

Zohoy’s Competitive Analysis (Detonka, Estruck’s competitor)

Zohoy established rapport with the readers and showed consideration for his fellow members through the use of the first person plural pronoun ‘ we ’ in Theme position. This finding contrasts with Yeung’s ( 2007 , p. 177) claim that the use of first person pronouns “does not seem to be a defining characteristic of business reports as claimed”. It also contradicts with Hyland’s ( 2005 : 14) argument that while ‘expert writers’ use personal pronouns and interjections to claim affinity with audience, students tend to underuse these features.

All the students applied their conceptual knowledge of marketing in order to construct statistical graphs that encompassed a complex array of elements and processes (Monteiro and Ainley 2006 ). The graph in Fig.  6 shows Hind’s analysis of Alfa’s advertising and promotion from period 6 to period 9. Advertising and promotion slopes represent relational attributive processes that are interpreted in terms of their degree of steepness (or vertical movement), whether steep upward or steep downward to represent an increase or decrease respectively. The slopes can be interpreted in natural language as “advertising and promotion [ Carrier ] will be [ Pr: Rel, Attrib ] gradually growing [ Attribute ] from periods 6 to 9”.

Hind’s analysis of Alfa’s advertising and promotion from period 6 to period 9

The graph includes six instances of Theme reiterations, as the Themes “Alfa’s advertising in period 6” and “Alfa’s promotion in period 6” are taken as the Themes of the ensuing ones for periods 7–9. Kress and van Leeuwen’s ( 1996 ) Ideal-Real compositions in images and text-images can be applied to the semiotics of marketing plan tables. The table in the tutor’s text 2 shows the calculations of hourly labour rates (Table  7 ).

The categories on the left represent the ‘Ideal’ since they are concerned with abstract technical entities- while the numerical values represent the ‘Real’ since they are concerned with practical or factual details. The tutor comments on the text following the table: “the hourly rate for estimating work will be charged at $28.00 + 25 % mark up = $36.50 per hour”. Whereas the clause “the hourly rate for estimating work” represents the Given information, “will be charged at $28.00 + 25 % mark up = $36.50 per hour” is the New information. The topical Given Themes in Table  7 are to the left side while the numerical values in the first ten rows represent Given information. The sum of these values in the last row, “$28.03”, represents New. The numerical values in marketing plan tables include not only New information but also historical Given information. The analysis of informational choices in tables and graphs extends Kress and van Leeuwen’s ( 1996 ) approach to the analysis of visual artefacts in terms of compositional zones. The SF-MDA of informational content in tables and graphs showed that left-hand and right-hand English language spatial dimensions do not necessarily correspond with the Given-New/ Ideal-Real compositions. This finding cannot be generalisable given the fact that a few students participated in the present study. They are, however, in line with Alyousef’s ( 2015 a, 2015 b) and Jones’ ( 2006 ) argument that an image or text occurring on the right side does not necessarily present New visual or verbal information. Table  8 includes 32 instances of Theme reiteration pattern, as each Theme in column 1 is implicitly reiterated four times (periods 6–9).

For example, “sales” in the first column is taken as the Theme of the ensuing ones: “ sales for period 5 will be $8,585,000,000. Sales for period 6 will be $9,014,250,000” and so on. Therefore, the topical Themes in column 1 function intrasemiotically with the values in the other columns to facilitate comparability.

The Themes in Table  8 , however, do not only function intrasemiotically but also intersemiotically through the interaction of the table and the accompanying text, which included two types of information: Given information elicited directly from the table (i.e. context) and the other representing New related information. In the latter type, New information is inferred from the table, thereby constituting intersemiotic enhancement relation. In other words, the table helped Nura in drawing conclusions in the orthographic text, as shown below (Given information in italics, New information in bold).

our margin is increasing in the next 4 years (Th) , reflect efficient operations and management (Rh). The expenses (Th) are lower than forecasted sales revenues for coming periods (Rh), which (Th) reflect increase in our income from operation (Rh). The income increases in the next years , the most obvious cause of that increase (Th) is lowering operating expenses (Rh).

Rheme conflates with New information in the text above. One notices that the italicized text clarified the information in the table. This is called an elaborating relation, and it refers to the same participants, processes and circumstances in the table. The reiteration of a theme in the text accompanying the graphs and the tables not only provides a strong topical focus by presenting additional Given information (extension), but also achieves other functions, including making further explanations (elaborating), providing interpretive analytical analysis and taking decisions by exhibiting viewpoints that assist in drawing conclusions (enhancing) inferred from the graphs and the tables, and which presented meanings that are entirely new (Alyousef 2015 a). As the accompanying text added New information based on the findings, a logico-semantic relation of extension exist between the two multimodal discourses and the text accompanying them.

Having presented and discussed the findings of the SF-MDA of the participants’ marketing plan, what follows is a conclusion and the theoretical and the pedagogical implications of the findings.

Conclusion and implications

The findings suggest that the students have managed professional workplace practices by showing their understandings of marketing as part of overall business management. This was achieved by engaging in analyses and planning, linked to what one wants to do with the company, which in turn could affect them in and beyond the university. All the three participants successfully completed their Business of Management (Marketing) undergraduate program.

The SF-MDA of marketing plan texts showed that they intertwine different thematic progression patterns. Marketing plan texts include the following key linguistic features

Extensive use of Theme reiteration pattern, followed by the linear Theme pattern

The use of imperative Themes in the marketing plan objectives and goals

Extensive use of textual Themes that expand a proposition, conjunctions that link two clauses through paratactic or hypotactic relations

The use of bulleted and numbered lists to facilitate recall and transition from prescription to action. Bullet points foreground key features of an aspect by truncating Themes and relational identifying processes, thereby encoding structural information in the most economical manner

The use of anticipatory it in Subject position to present viewpoints and to express their attitudes towards particular points through the use of projecting clauses.

The use of multiple Theme pattern is one of the characteristic features of this genre, as writers need to persuade their readers to the viability of their plans. This pattern is the most difficult one for academic writing students because they need to list a number of different pieces of information. Students’ language proficiency and their previous academic experiences may have influenced their use of linear and multiple-Theme patterns. Multiple-Theme pattern was mainly used to

Discuss key features of items

Describe the qualifications of entrepreneurs and their experiences

Discuss the reasons underlying positive outlook for the industry in general and the researched company in particular

List the assumptions through which the plan was based on, objectives, and the recommendations,

List strengths, weaknesses, opportunities, and threats (SWOT) of the researched company.

List key issues from SWOT and the main findings of competitor analysis.

The SF-MDA of the visual semiotics showed marketing plan texts extensively employ structural condensation in the graphs and tables to encode numerical data in the most economical manner. Unlike orthographic texts, rhematic statuses in tables and graphs are contingent on the material value of the message, whether it is known before or not. Meanings are created in visual semiotic resources not only intrasemiotically but also intersemiotically through the interaction of the graph and the tables and the text surrounding them.

The participants made meaning through the intersemiotic shifts (or resemiotisation processes) from diagrammatic and tabular forms to textual. A logico intersemiotic semantic relation of extension exists between the tables and graphs and the text accompanying them since the latter provides New information based on the content of the visual semiotic mode.

This paper contributes to our understanding of thematic progression, the composition of information value, and the logico-semantic relations in marketing plans. A number of pedagogical and theoretical implications can be suggested as an outcome of this research study. The SF-MDA of informational choices in the multimodal business artefacts extends Kress and van Leeuwen’s ( 1996 ) functional interpretations of visual artefacts in terms of compositional zones. The SF-MDA of these artefacts indicates that text-based analyses is facilitated by the participants’ intuitive interpretation (or reading path) of the meaning-making processes. As thematic progression patterning plays a vital role in comprehending a text and in providing a naturally flowing text, it can be emphasised in the teaching and learning of writing, particularly in ESP/EBP courses. Diversification of the thematic choices can lead to a well constructed text. ESP/EBP instructors need to give more attention to the process of writing rather than the product. Tutors can draw students’ awareness to the different thematic choices available for them. This can be followed by class activities that include identifying and analysing thematic progression patterns. Marketing texts include a large number of implicit linguistic resources which can be made explicit in ESP/EBP classes. Students can, through practice, easily control the flow of their texts. As Butt et al. ( 2009 : 154) argue that students can consciously organize their texts more effectively once they “explore how patterns of Theme and Rheme enable the progression of different types of texts”. Moreover, it is essential for ESP/EBP students to understand and interpret the logical relations between tables and graphs and the accompanying text. Tutors can introduce the ways of expanding the meaning-making potential in these visual semiotic resources by presenting samples of elaboration, extension, and enhancement relations. They can start first with the simplest one, extension, and then move to the others. If these implications were made explicit, student’s learning experiences and their understanding of the meaning making resources may be greatly enhanced and, in turn, affect them in and beyond university.

Finally, the study is limited to five individual marketing plan reports and, therefore, the findings are not based on a representative sample of the discipline’s academia.

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The author expresses his appreciation to the Deanship of Scientific Research at King Saud University and to the Research Center at the Faculty of Arts for funding the current research study.

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Hesham Suleiman Alyousef is an assistant professor at the Department of English Language and Literature at King Saud University in Riyadh, Saudi Arabia. He completed his Master’s degree in applied linguistics in 2007 at King Saud University. He worked as an MA thesis examiner during his Ph.D. candidature and as an academic editor for the Asian ESP Journal. He has published a number of papers in refereed academic journals, as well as in journals listed in Thomson’s Institute for Scientific Information (ISI) database. His research interests include systemic functional linguistics, academic literacies, metadiscourse, multimodal discourse analysis, reading comprehension, and the use of Web 2.0 technology in higher education. He has more than 25 years of experience in teaching ESL/E FL students.

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How to Conduct Online Discourse Analysis

• By: Janet Smithson
• Product: Sage Research Methods: Doing Research Online
• Publisher: SAGE Publications, Ltd.
• Publication year: 2022
• Online pub date: July 12, 2022
• Discipline: Sociology , Education , Psychology , Health , Anthropology , Social Policy and Public Policy , Social Work , Political Science and International Relations , Geography , Criminology and Criminal Justice , Nursing , Business and Management , Communication and Media Studies , Counseling and Psychotherapy , History , Economics , Marketing
• Methods: Discourse analysis , Internet research , Naturally occurring data
• DOI: https:// doi. org/10.4135/9781529607482
• Keywords: discourse , internet Show all Show less
• Online ISBN: 9781529607482 More information Less information

The use of Discourse Analysis (DA) applied to online data is increasingly popular as a way of studying how people interact and communicate via online, or digital, platforms. This How-to Guide provides an introduction to what Online Discourse Analysis (ODA) is, how traditional DA has been applied to a wide range of online sites and interactions, and what new challenges and possibilities this has brought to our understanding of human communication and behaviour. This guide explains what types of online platform are suitable for ODA, how to choose what sort of digital site to study and what sort of topic to research using ODA. Practicalities such as how to collect and store online data, ethical issues to consider, and methodological challenges are all briefly covered. The guide concludes with a few suggestions about how to actually start doing ODA on your selected data.

Learning Outcomes

By the end of this guide, readers should be able to:

• Identify suitable internet sources for Discourse Analysis (DA), including online interactions and media publications
• Know how DA can be used to understand how people interact online to construct and deconstruct social reality
• Use recommended tools to collate sources and keep track of DA
• Understand the ethical issues around using online data in discourse research
• Know how to start conducting a DA of online data

What Is Online Discourse Analysis and When Would You Use It?

Online Discourse Analysis (ODA) is the practice of Discourse Analysis (DA) applied to online, or digital, data. This mostly applies to text produced or reproduced online, and to communication that takes place within a digital environment. There are many versions of DA used across the disciplines of humanities, social sciences, and linguistics. Popular approaches include Potter and Wetherell (1987) , Edwards and Potter (1992) Foucaudian DA ( Arribas-Ayllon & Walkerdine, 2008 ; Foucault, 1972 ), and Critical Discourse Analysis which has a broader interest in context and power ( van Dijk, 2016 ). Multimodal DA incorporates visual aspects of platforms – for example, logos, images, typography – into the analysis, also attention to features of online talk such as audiencing ( Rose, 2016 ) – how a site or post is seen by different audiences, at different times.

Discourse Analysts share a set of assumptions about language practices – an ‘analytic mentality’. Language is understood to be an activity through which people achieve something – so language is viewed not as a representation of an external reality, but the medium through which we construct our understanding. DA is therefore focused on the functions of talk as a social action or behaviour – what is the speaker/writer/poster doing with this talk? Language is understood to be situated in a particular context – so the exact location of talk is important – for ODA this means that the nature of the online setting is a crucial part of the analysis. The content of the talk cannot be understood without reference of the environment of the talk, including previous talk or activity. Talk (spoken or written) is constructed in a specific context for a particular purpose , and it is constructive in that we use language to build our understanding of the world in general, and of specific events.

Advantages of online data for DA researchers include accessibility, lack of need to record or transcribe, and sheer quantity of available text about an enormous range of topics. Another benefit of ODA is that all sorts of people, including those reluctant to sign up for research studies, go online to find others with similar experiences or problems, to share experience, support and advice, or to socialise, date, or make new friends.

Section Summary

• ODA is the practice of DA applied to any type of online, or digital, data, especially internet-mediated communication.
• ODA can be a useful approach for studying how people interact online.

What Are Suitable Internet Sources for DA?

DA can be applied to a wide range of written text and spoken talk. Suitable internet sources include almost any platform, or site, or technology, where people use language to interact online. Text online occurs on any platform where users can type in their comments or join an online typed conversation. Online talk interaction may take place via video-mediated interaction on Zoom, Skype, MSTeams, WhatsApp, and so forth. DA also study wearable technology, health apps, and instant messaging on phones. In fact, any emerging technology that contains written or spoken language can be studied on ODA. You can see from this that the range of talk and interaction that comes under the broad category of Online or Digital is enormous and expanding rapidly.

• Suitable sources for ODA include any interaction using technology where people talk or post written text to each other.
• Older technologies such as television programmes are suitable for analysis with ODA.
• It is also possible to analyse interaction on new technologies such as wearable apps or medical technology.

Types of Talk and Digital Interaction – Some Important Distinctions

A key point to remember is that each of these digital sites, or platforms, has different technological features that need to be considered in ODA. In this next section, I outline some important concepts and distinctions, namely:

• Synchronous versus Asynchronous
• Research-designed versus naturally occurring data
• Spoken talk versus written text
• Content/information versus Interaction
• Formal versus informal talk

Synchronous Versus Asynchronous

Most ‘real life’ communication occurs synchronously , that is, in ‘real time’, for example, people having a conversation, or participating in a focus group, and this was historically the main focus of DA. Synchronous conversations or interactions occur online too, for example a group of participants all logged into a discussion, posting their comments and interacting directly with each other, for example students having a virtual lesson, all typing into chat, or by talking on videoconference, for example, a doctor–patient Skype consultation. In asynchronous communication, one person provides information, and then there is a time lag before the recipients take in the information and offer their responses. This is very common online, for example, a student message board may have comments posted over a week or over several weeks. A Facebook discussion may be contributed to over a few hours. Sometimes the distinction may not be clear, for example a fast-moving Twitter thread could be synchronous, but a slow-moving one might be asynchronous.

Research-Designed Versus Naturally Occurring Data

Discourse Analysts have a strong preference for ‘naturally occurring’ data ( Potter, 2016 ), by which they mean talk that occurs outside a research setting – so a conversation between friends, a group discussion in a tutorial, or a recorded clinical encounter is favoured over a traditional research interview. Much online data – Twitter, forum talk, WhatsApp, or Discord group chat, are naturally occurring and easily accessible for the researcher. A student online tutorial, for example, using MSTeams, would count as natural data and could (subject to participant agreement) be recorded for research. It is also possible to set up research online and study this using DA – for example, a Zoom interview or a Zoom focus group.

Spoken Talk Versus Written Text

The majority of ODA has, until recently, been conducted on written text gathered from various possible internet sites. Relatively little attention was paid to spoken interaction – talk – on the internet. This changed during the COVID-19 pandemic, when suddenly much of the world’s interaction shifted online, and most obviously, led to a rise in video-conferencing videochat use. Clinicians, schools, universities, charities, local councils, and all sorts of workplaces have shifted to working via virtual platforms (Zoom, MS Teams, Skype), while online socialising has utilised these same virtual conference platforms, and also less formal videochat and other socialising apps (WhatsApp, Houseparty, Tiktok) and gaming platforms ( Liddell, 2020 ). This has led to an expanded interest in analysis of videoconference and videochat interactions.

Content/Information Versus Interaction

Text or talk online may be informational (such as a government, health, or news website), commercial (Ebay and other selling sites), or designed for interaction (Facebook, Twitter, talk forums). Many digital sites are a mixture of information and communication, so you might study below-the-line responses to news, YouTube comments posted under videos, perhaps together with analysis of the original information. Different schools of DA have focused on text or talk: Foucaudian DA typically analyses broad concepts of societal power, historical structures, organisations, and hierarchies. This is often applied to informational texts. Discursive Psychology, in contrast, focuses specifically on the interactions between participants, drawing on concepts from Conversation Analysis to do this, and is more suitable for interactional talk.

Formal Versus Informal Talk

Another distinction often attended to in DA is whether the context of the talk is formal or informal. For example, a job interview or a consultation with a medical practitioner, follows a known ‘script’ that all participants tend to follow, and it is viewed as problematic when they move away from this script. Informal talk, such as a WhatsApp group chat, will be far less standardised or scripted.

• ODA can be used to study how people communicate either by typing text or by talking on videoconferencing or videochat platforms.
• ODA can be used for research activities set up online, or to study existing online data.
• There are a variety of different types of data sources that can be used for ODA, including synchronous and asynchronous data, research-designed and naturally occurring data, spoken talk and written text data, content/information and interaction data, and formal and informal talk data.

Theorise How Language in Online Spaces Constructs and Deconstructs Social Reality

An important aspect of doing a DA is the linking of relevant theory to data analysis, moving beyond a description or summary of phenomena to providing a theoretically informed analysis or explanation ( Antaki et al., 2003 ). Some examples of how theoretical aspects of DA can be applied to online topics and platforms include:

DA of online communication can explore how people socially construct or make sense of their lives and their experiences or conditions. ODA has been used to study social constructions of health and illness, with a focus on patient, or layperson experience. People experiencing a shared problem or health condition will talk to each other very differently to how a health professional would describe the situation, and the conversation may be quite different from what would be told in a standard research interview. How do people online collaboratively construct categories and practices around their experiences? For example, Horne and Wiggins (2009) studied how people talked about feeling suicidal on an internet forum.

A detailed study of interactional patterns online can explore the ways in which the technology itself may encourage or lead to specific digital behaviours, such as trolling, ghosting, harassment, or bullying. For example, Licoppe (2021) investigated how people ghost others on Twitter threads.

DA is used to highlight how power dynamics operate, and can focus on whether online spaces might be more egalitarian interactional spaces, or whether they perpetuate, encourage, or challenge inequality and dominance. Feminist researchers have used ODA to highlight issues of sexism and abuse online, for example Tiidenberg (2017) , studied ‘visual discourses’ of gender and ageing on Instagram, and also to demonstrate ways of combating sexism online ( Rothschild, 2021 ). Others have studied racism, for example Lawson (2020) investigated callout strategies and racism in the online beauty community, studying influencers on YouTube, Twitter, and Reddit.

Positioning or subject positioning is a core concept in DA ( Harré & Van Langenhove, 1999 ). Positioning theory is concerned with explicit and implicit patterns of reasoning that are evidenced in the ways people act towards each other – including how they interact in talk. The patterns of interaction – how people position themselves in and through their talk, and how they are positioned by other participants, can show us what people’s priorities are, who and what they focus on, and how they maintain conflicts and alliances. In online talk, we can analyse when and exactly how some participants are attended to more than others. How do they achieve this? Can this be shown just in the nature of the talk, by looking at who responds, and how quickly, or do they draw on evidence of their ‘external’ characteristics –gender, age, ethnicity, expertise?

You might be interested in argumentation or opinion formation in online chat or virtual tutorials. How do participants make their views known? What happens to a controversial view? How do people respond? This will be very different in anonymous online interaction, for example in a chat forum with usernames, to a student tutorial where people know each other. Recently, people have been studying precisely how (mis)information about COVID-19 and vaccines is constructed and spread across the internet.

One feature of online interaction that has garnered much interest among discourse analysts is the shadowy nature of who the audience is and whether listeners respond or merely ‘lurk’. Some types of digital interaction are designed for recipients who are effectively unknown, such as people who are ‘lurkers’ on large sites. These lurkers do not tend to engage in the interaction, but rather simply read posts or messages. Therefore, they are not just anonymous strangers, but they are also invisible. Speakers or posters may be addressing a known audience, an imagined one, and/or an unspecified invisible audience. These issues of participation frameworks and recipient design are an interest area in Discursive Psychology.

• ODA draws on standard DA concepts such as understandings of power structures and hierarchies, subject positioning, to make sense of online text and talk.
• ODA is used to study the details of exactly how people interact online.
• ODA can highlight complexities of online talk and how it is different from face-to-face interaction, for example, in terms of perceived participation and audience.

Ethical Issues in ODA

There are ethical considerations to be considered in general for online research and a few specific challenges for ODA. As technological change occurs, it impacts on good ethical practise, and researchers need to be flexible and adapt to changing situations. There are many guidelines for ethical practise in online research, for example from the British Psychological Society (2021) .

The Public/Private Distinction and Informed Consent

Do you need to gain explicit informed consent from online participants? Legally, things posted on public sections of the internet – written text, or video – are viewed as published in the public domain, and as such do not need individual posters’ consent for reuse, just as you could repeat something published in a newspaper. This approach was common previously in online research, with some researchers, such as Danah Boyd (2008) arguing that this type of research functions like an ethnography, observing behaviour that is produced in a public space.

However, many people in practice use aspects of the internet as though they are in a private club or group, for instance on support forums, and as such it is good practice to request permission to reuse data from these platforms. Sometimes it is possible to request permission from site owners, such as a forum owner or moderator, and sometimes it is more appropriate to request permission directly from participants, perhaps by posting about the research on the site. This is particularly important for sensitive or personal data, and also with vulnerable populations, such as children or adolescents. Personal Blogs are simpler in many bloggers want to publicise their content or cause, so can be approached directly for research participation.

In some sites, such as Facebook, users and groups set their own privacy and access boundaries, but you still might want to request permission before analysing data from an individual’s Facebook page. A public Facebook Group, however, might be reasonably viewed as publicly available for analysis.

If you do get participant consent, you should provide the normal expectations of providing a reasonable opportunity for them to withdraw from the research if they change their mind. If you are analysing group data – for instance, a forum discussion, you will need to consider appropriate deadlines which are fair to participants. This would be the case for any group research, such as a real-life focus group, so is not specific to online research groups.

Challenges of Anonymity

It is important to remember that the internet is very easily searchable, with increasingly powerful search engines. Reproduction of text is therefore potentially searchable, even if you anonymise the data according to traditional research norms – for example, changing names/pseudonyms and taking out dates and identifying features. Possible answers to retain participant anonymity include:

• Using screenshots or transcripts with more details blanked out.
• Use of screenshots or full transcripts for analysis but only some features central to analysis being reproduced in publications.

Authenticity: Fake Posts and Constructed Identities

A possible downside of online methodologies is the potential for people contributing without being honest about their identity, and perhaps providing false information. This may be particularly relevant for some research, and may matter less for others – for instance, if you are researching a taboo or difficult topic, the freedom to post more unacceptable views may be useful, and participants’ exact ‘real life’ identities may be less important. In DA, the focus is on text as a behaviour and a construction, and the exact details of participants become less crucial. This discursive understanding of talk construction may need modifying if your research includes vulnerable participants, for example, children or people with mental health problems.

In general, in research ethics, you need to try and maximise benefit while minimising harm ( British Psychological Society, 2021 ). Ethics of online research is a developing area, with various grey areas that are open to interpretation, so your ethics procedure needs to be clear about how you have considered these various aspects and taken reasonable actions.

• The distinction between what counts as a public and private space can be blurred on the Internet: legally, an Internet discussion may be public, but participants may view their online group as a private space.
• Ethically, the researcher should consider participants’ intentions and expectations when justifying use of data. This may include specifically requesting permission to use data in research even if the data are publicly accessible.
• Particular care needs to be taken when researching talk by vulnerable participants, such as children.
• In DA, talk is viewed as co-constructed in a particular context for a particular purpose. This means that the focus of analysis is the text, or data, not the individual who produced it, so the need for specific participant demographic details may not be as relevant as it is for other research approaches.
• Remember that internet search engines make it easy for readers to find your original source data, including personal details you may have cut out.

Organising Your Sources, Data, and Analysis.

It is very easy to cut and paste from the internet, but for ODA you need to be clear where exactly your data originates from. As the Internet changes all the time, you need to note not just the exact location of your data, for example, the URL, but also the date/time of download.

You should download and save audio or video recordings of your source, for example, a YouTube video, or a screenshot of text. For DA, the exact detail of the talk is vital, so even if you transcribe or code your data, you need to save the source text/recording until all possible analysis/writing up is completed. For audio/video recording. Many videoconferencing systems such as Skype, Zoom, and so forth, now include recording functions. It is also possible to blank over names, faces, and identifying features if you need to play recordings to a DA audience.

Voice recognition software is improving rapidly, so there are increasing options for Auto transcribe. There are specialist auto-transcription software packages, ExpressScribe for instance, but lately Zoom, Skype, and Teams provide auto-transcription. For a DA, you need more accuracy than an auto-transcribe function will normally provide, so consider the auto-transcription as a first draft, not a final transcription

There are various tools to help manage online data storage and analysis. Qualitative researchers increasingly use computer-assisted qualitative data analysis software (CAQDAS) to support their qualitative analyses, for example Nvivo and Atlas-ti (QSR International). These software programmes were originally designed for qualitative data in text form but has expanded to include video and audio recordings. Discourse Analysts have been slow to use these, as they tend not to want to use the auto-coding functions, but they are also suitable for storage and retrieval of online data, including textual, visual, and audio files. ( Paulus et al., 2015 ) This can be very useful for multimodal DA.

When retrieving, storing, and saving your data, be aware that for DA you need more context and detail than for many other qualitative approaches. Aspects of the content you often need to include in your DA, and in your records, include details such as punctuation, and paralinguistic features (hashtags, emoticons, epigraphs). Screenshots of written text preserve more of these details than transcribed versions of online talk.

• For ODA, you need to save an exact recording or transcription of the text or talk to be analysed, either by audio- or video-recording, or by screenshots, or by doing a detailed transcription.
• You should note down site (e.g., the URL) and date of download of your data.
• You can use software to help you store, record, transcribe, and analyse your data.
• For DA of online text, you may want to include paralinguistic details such as hashtags, emoticons, images, and sound clips.

Getting Started With Your ODA

As should be clear by now, there is an enormous and expanding choice of possible topics and platforms to study using ODA. So, you have located your topic, found your online source/s, downloaded your data, saved it, considered the ethics of data collection, use, and storage… what do you do now? You may want to follow a set of DA guidelines – accessible introductions and guidelines include Gee (2014) , Georgaca and Avdi (2012) . However, these introductory guidelines to DA should be understood as an aid to getting started rather than a set of rules to be narrowly followed.

Some Strategies for DA of Online Data

• Consider the context of the talk: is it formal or informal, known participants, anonymous posters?
• Consider who the talk is designed for. Does it assume a known group of participants, for example, a regular set of posters to a forum?
• What is the purpose of the talk? Is a blogger trying to sell their products, or educate people about their health condition, or challenge the political status quo?
• Look at how participants position themselves – how do they introduce and frame their opinions? What do they draw on as relevant? To what effect?
• Take time to consider what assumptions are unchallenged in the data, which speakers/posters or statements are responded to, and which have been ignored or minimised.
• Consider how the exact questions asked, and the first responses, affect subsequent responses or discussion. Which versions of participants’ experiences are encouraged, and which are ignored?
• Look out for how many people in a group join in a particular discussion. Are there markers of agreement or dissent?
• Are there dominant participants? How do they achieve this dominant status?
• DA, including ODA, does not come with a specific set of rules to follow. It should be understood as a methodology or an approach to understanding (online) talk and text.
• To get started in ODA, you can draw on wider DA interests and principles, but need to consider how these may be relevant for your specific online context.
• In online DA, as with all DA, attention needs to be paid to implicit as well as explicit power hierarchies, assumptions, and norms. Who benefits from this talk or text, who is silenced, who does not even attempt to join?

This guide has introduced ODA and explained how traditional approaches to DA have been adapted for many types of technology-mediated communication. The guide has shown how DA can be applied to a wide range of online sites and interactions to make sense of both written text and spoken talk online. The specific methodological, practical, and ethical challenges this brings have been introduced. This guide has suggested what sorts of topic can be studied, and what types of online platform are suitable for this methodology. Practicalities around how to collect and store online data and suitable software to help with ODA are covered. The guide concludes with suggestions about what to focus on when starting your own ODA on your selected data.

Multiple Choice Quiz Questions

1. Which of the following is an example of asynchronous interaction?

Incorrect Answer

Feedback: This is not the correct answer. The correct answer is B.

Correct Answer

Feedback: Well done, correct answer.

2. Whose consent do you not need to consider when using data from an online site in research?

3. Which of the following is the best example of naturalistic data in DA?

4. What ethical consideration might you include when using data from on an online forum where young adults discuss their experience of eating disorders?

Feedback: This is not the correct answer. The correct answer is C.

5. ODA is useful for studying:

Feedback: This is not the correct answer. The correct answer is A.

Further Reading

British Psychological Society ( 2021 ), Ethics guidelines for internet-mediated research .

Meredith , J. , Giles , D. & Stommel , W. ( 2021 ), Analysing Digital Interaction . Palgrave Macmillan .

Web Resources

http://www.discourseanalysis.net/

http://www.discourses.org/resources/websites/

https://www.open.edu/openlearn/tags/discourse-analysis

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