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• Critical Discourse Analysis | Definition, Guide & Examples

Critical Discourse Analysis | Definition, Guide & Examples

Published on 5 May 2022 by Amy Luo . Revised on 5 December 2022.

Discourse analysis is a research method for studying written or spoken language in relation to its social context. It aims to understand how language is used in real-life situations.

When you do discourse analysis, you might focus on:

• The purposes and effects of different types of language
• Cultural rules and conventions in communication
• How values, beliefs, and assumptions are communicated
• How language use relates to its social, political, and historical context

Discourse analysis is a common qualitative research method in many humanities and social science disciplines, including linguistics, sociology, anthropology, psychology, and cultural studies. It is also called critical discourse analysis.

Table of contents

What is discourse analysis used for, how is discourse analysis different from other methods, how to conduct discourse analysis.

Conducting discourse analysis means examining how language functions and how meaning is created in different social contexts. It can be applied to any instance of written or oral language, as well as non-verbal aspects of communication, such as tone and gestures.

Materials that are suitable for discourse analysis include:

• Books, newspapers, and periodicals
• Marketing material, such as brochures and advertisements
• Business and government documents
• Websites, forums, social media posts, and comments
• Interviews and conversations

By analysing these types of discourse, researchers aim to gain an understanding of social groups and how they communicate.

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Unlike linguistic approaches that focus only on the rules of language use, discourse analysis emphasises the contextual meaning of language.

It focuses on the social aspects of communication and the ways people use language to achieve specific effects (e.g., to build trust, to create doubt, to evoke emotions, or to manage conflict).

Instead of focusing on smaller units of language, such as sounds, words, or phrases, discourse analysis is used to study larger chunks of language, such as entire conversations, texts, or collections of texts. The selected sources can be analysed on multiple levels.

Discourse analysis is a qualitative and interpretive method of analysing texts (in contrast to more systematic methods like content analysis ). You make interpretations based on both the details of the material itself and on contextual knowledge.

There are many different approaches and techniques you can use to conduct discourse analysis, but the steps below outline the basic structure you need to follow.

Step 1: Define the research question and select the content of analysis

To do discourse analysis, you begin with a clearly defined research question . Once you have developed your question, select a range of material that is appropriate to answer it.

Discourse analysis is a method that can be applied both to large volumes of material and to smaller samples, depending on the aims and timescale of your research.

Step 2: Gather information and theory on the context

Next, you must establish the social and historical context in which the material was produced and intended to be received. Gather factual details of when and where the content was created, who the author is, who published it, and whom it was disseminated to.

As well as understanding the real-life context of the discourse, you can also conduct a literature review on the topic and construct a theoretical framework to guide your analysis.

Step 3: Analyse the content for themes and patterns

This step involves closely examining various elements of the material – such as words, sentences, paragraphs, and overall structure – and relating them to attributes, themes, and patterns relevant to your research question.

Step 4: Review your results and draw conclusions

Once you have assigned particular attributes to elements of the material, reflect on your results to examine the function and meaning of the language used. Here, you will consider your analysis in relation to the broader context that you established earlier to draw conclusions that answer your research question.

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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?”

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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.

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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

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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?

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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

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

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Discourse analysis: Step-by-step guide with examples

What is a discourse analysis, the application of discourse analysis in the academic thesis, discourse analysis with maxqda.

• Step 1: Importing data
• Step 2: Coding data
• Step 3: Creating Codebook
• Step 4: Visualize data

Literature about MAXQDA

Tuesday, September 19, 2023

MAXQDA supports various methodological approaches, including discourse analysis. This guide will introduce you to the tools of MAXQDA, which are ideal for performing discourse analysis with MAXQDA quickly and easily. MAXQDA is a qualitative data analysis software that helps you import, code, and identify patterns in your discourse.

Discourse analysis is a multidisciplinary method used in the humanities and social sciences to develop a deeper understanding of the interactions between language, society, and culture. It focuses on the study of linguistic expressions, structures, and practices in order to capture social meanings and power dynamics. Both verbal and nonverbal communication are considered. The overarching goal of discourse analysis is to explore how discourses influence the construction of knowledge, identities, and social relations. It enables the study of the role of language and communication in shaping and influencing social reality. Overall, discourse analysis makes a valuable contribution to the study of social phenomena and processes by providing an in-depth understanding of how language and communication are used to create meanings, shape social relationships, and establish social power dynamics. Discourse analysis contributes to critical reflection and knowledge acquisition in various academic disciplines.

A primary motivation for using discourse analysis is the ability to uncover dominant discourses, ideological assumptions, and power structures in texts, media content, or political speeches. Discourse analysis allows researchers to better understand and critically reflect on the role of language and discourse in society. Another important area of application of discourse analysis in dissertations is the study of the relationship between discourses and identity constructions. For example, gender roles, ethnic identities, or sexual orientations can be studied. Discourse analysis can help to understand how identities are negotiated, constructed, and reproduced in specific social contexts. Another area of application in dissertations is the study of discourses in the media. The analysis of media discourses makes it possible to identify, critically expose and reflect on patterns and trends in reporting. This can contribute to a better understanding of the media’s role in constructing and disseminating discourses. In summary, discourse analysis offers a valuable methodological perspective for the study of complex social phenomena in the context of academic work.

Researchers typically follow these steps in discourse analysis: defining the research question, selecting relevant textual data, coding and categorizing the data, analyzing patterns and meanings within the discourse, interpreting the results, and documenting their findings in written form. The specific steps may vary depending on the research question and methodology.

As mentioned earlier, there are clear advantages to using software like MAXQDA to conduct discourse analysis. With MAXQDA, you can segment data, code it, and develop analytical ideas all at the same time. This makes the process more efficient and allows you to refine your theoretical approaches in real time. If you do not have a MAXQDA License yet, download the free 14-day trial to get started:

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Step 1 of the discourse analysis with MAXQDA: Importing data

Importing data into MAXQDA is a crucial step in beginning the analysis of qualitative data. MAXQDA provides several options for importing data into the program, allowing you to effectively organize your research materials. You can import different types of data, such as text documents, transcripts, media content, or existing MAXQDA Projects. MAXQDA gives you the flexibility to import both individual files and entire folders of data, which is especially helpful when working with large data sets. The import process is designed to be simple and user-friendly, making it easier for you to work with your data.Another advantage of MAXQDA is that it supports a wide variety of file formats. You can import files in various formats, including TXT, DOC, PDF, MP3, MP4 and many more. This versatility allows you to work with different types of data and incorporate different media into your analysis.Importing your data into MAXQDA makes it structured and accessible for further analysis. Within MAXQDA, you can organize, code, and link your data with other analytical tools. This makes it easier to navigate and access relevant information during the analysis process.Overall, importing data into MAXQDA is an efficient way to manage your qualitative research materials and prepare them for analysis. It serves as a critical first step in launching your project in MAXQDA and taking full advantage of the program’s extensive analytical capabilities.

Importing data into MAXQA plays a crucial role in conducting discourse analysis. With MAXQDA, you can segment your data into documents and annotate them with relevant metadata such as title, author, and date. This allows you to organize your texts during the analysis phase. You can sort, filter, and group your data based on various criteria to access specific texts. In addition, MAXQDA provides the ability to annotate the imported text with notes, comments, or memos. This feature is invaluable for capturing important information, thoughts, or interpretations that arise during analysis. You can document your observations and insights directly in MAXQDA, thus fostering a comprehensive understanding of the discourse being analyzed.In MAXQDA, you can assign meaningful titles to your data and include relevant metadata such as author and date in the document names. This ensures a clear organization of your texts during the analysis phase. You can sort, filter, and group your data according to various criteria to access specific texts. In addition, MAXQDA allows you to annotate the imported texts with comments and notes using memos. This feature is very useful for capturing key information, thoughts, or interpretations that emerge during the analysis. You can document your observations and insights directly in MAXQDA and develop a thorough understanding of the discourse being analyzed. Importing data into MAXQDA is fundamental to conducting a systematic and comprehensive discourse analysis.The structured organization of data in MAXQDA facilitates the effective application of various analysis methods and techniques. You can create codes to identify and analyze important themes, terms, or patterns within the discourse. Importing data into MAXQDA provides a central platform where you can manage, analyze, and interpret your data. This greatly streamlines the entire process of discourse analysis, allowing you to make informed statements about social meanings, power dynamics, and identity constructions within the discourse you are analyzing.

Step 2 of the discourse analysis with MAXQDA: Coding data

Coding data in MAXQDA plays a critical role in the analysis process. Coding involves identifying and marking specific themes, categories, or concepts within the data. This allows researchers to systematically organize and extract relevant information from the data. In MAXQDA, different types of data can be coded, such as text passages, images, videos, or audio files. Codes can be used to associate these data segments with specific content or meanings. Researchers can use codes to identify and mark certain phenomena or themes in the data, allowing for targeted access later. Coding in MAXQDA allows researchers to identify complex relationships and patterns within the data.By linking and combining codes and organizing them hierarchically, researchers can establish relationships between different elements. These connections provide new insights and help understand the relationships within the data. The coded data can be further used in MAXQDA for additional analysis. For example, complex queries or filters can be applied to examine specific aspects of the discourse in detail. By analyzing the coded data, researchers can identify patterns, trends, and significant relationships that lead to valuable insights.MAXQDA provides an intuitive and easy-to-use platform to efficiently perform the coding and analysis process. The program offers several tools and features that allow researchers to customize the coding process and tailor the analysis to their specific needs. Overall, coding data in MAXQDA is a critical step in analyzing and understanding qualitative data.

Coding data in MAXQDA allows researchers to identify and analyze specific discursive elements such as themes, arguments, or language strategies in the texts under study. To code data in MAXQDA, researchers can select relevant text passages and assign them codes that represent specific meanings or categories. These codes can be organized hierarchically to illustrate relationships between different discursive elements. In addition to coding, MAXQDA offers features such as text annotation, the ability to create memos, and options for visual data presentation at later stages. These features facilitate the organization and interpretation of coded data, enabling researchers to gain deep insights into the discourse under study and to visualize their findings. MAXQDA provides a comprehensive and efficient platform for coding and analyzing data in discourse analysis.

Step 3 of the discourse analysis with MAXQDA: Creating Codebook

A Codebook in MAXQDA defines codes for units of meaning within data. It enables structured and consistent coding, improves traceability and reproducibility, increases the efficiency of data analysis, facilitates comparisons and cross-references between codes and data, and provides flexibility and adaptability. In summary, a codebook promotes structured, consistent, and efficient data analysis, improving traceability and identification of relationships and patterns.

A Codebook is also very useful for discourse analysis in MAXQDA. Here are some reasons why:

• Structured coding of discourse features: A Codebook establishes uniform rules and definitions for coding data. This ensures that coding is structured and consistent across researchers and stages of analysis. This increases the reliability of results and facilitates the comparison and integration of data.
• Improved traceability and reproducibility: By clearly defining the codes and their use in the Codebook, the traceability of the coding process is improved. Other researchers can understand and trace the coding, increasing the reproducibility of the analysis. In addition, a Codebook facilitates effective collaboration and sharing of data and analysis among researchers.
• Identification and comparison of discourse patterns: A Codebook allows for the systematic identification and comparison of discourse patterns. This makes it possible to identify connections, patterns, and differences in the data, thus facilitating the interpretation of the results.
• Efficient data analysis: A Codebook provides a structured view of the codes used and their meanings. This allows researchers to work more efficiently by applying the codes quickly and specifically to relevant data. Using a codebook saves time and makes it easier to organize and navigate the coded data.
• Flexibility and adaptability: A Codebook in MAXQDA is flexible and customizable. Researchers can add, modify, or remove codes to meet the needs of their specific research questions. This allows for dynamic and iterative data analysis, where the Codebook can be continually updated and expanded.

In summary, a well-designed codebook in MAXQDA promotes structured, consistent, and efficient data analysis.

Step 4 of the discourse analysis with MAXQDA: Visualize data

MAXQDA offers a wide range of visualization tools to help you present your research data in an engaging and meaningful way. These include not only different types of charts, such as bar or pie charts for visualizing numerical data, but also other innovative visualization tools that help you identify and analyze complex relationships.

Code Matrix Browser

With the Code Matrix Browser , in MAXQDA, you can visually display and analyze the occurrence of codes in your data. This feature is invaluable for identifying similarities, differences, and patterns in discourse. Here are some of the ways the Code Matrix Browser can help you:

• Visualization of codings: The Code Matrix Browser displays a matrix where codes are arranged along the rows and documents along the columns. This visual representation allows you to quickly see which codes were used in which documents. This allows you to identify similarities and differences in the coding, which makes it easier to make connections.
• Pattern recognition: By analyzing codings in the Code Relations Browser, you can identify patterns in discourse. For example, you can observe which codes are particularly prevalent in certain documents. These patterns may indicate important themes, arguments, or language strategies, helping you to develop a more comprehensive understanding of the discourse.
• Comparison: With the Code Matrix Browser, you can compare how often certain codes were assigned in each document and display the corresponding information in the matrix. This allows you to analyze relationships between different elements in the discourse and to make connections between different topics or arguments.

Code Relations Browser

The Code Relations Browser , in MAXQDA allows you to visually display and analyze the connections and dependencies between the codes in your discourse. This feature is extremely valuable for understanding the interactions and hierarchy between codes. Here are some of the ways the Code Relations Browser can help you:

• Visualize code relationships: The Code Relations Browser visually displays the relationships between codes. You can see which codes are linked and how they are related to each other. These relationships can be hierarchical, associative, or several other types. This visual representation helps you better understand the structure and organization of codes within the discourse.
• Analyze interactions: The Code Relations Browser lets you analyze the interactions between codes. You can observe which codes occur frequently or how they influence each other. This can help you identify specific themes, arguments, or concepts in the discourse and examine their interrelationships. Analyzing these interactions can provide a deeper understanding of the discourse and the connections between codes.

The Code Map in MAXQDA visualizes selected codes as a map, showing the similarity of codes based on overlaps in the data material. Each code is represented by a circle, and the distance between the circles indicates their similarity. Larger circles represent more instances of coding with the code. Colors can highlight group membership, and connecting lines indicate overlap between codes, with thicker lines indicating more significant overlap.Visualizing the similarities between codes in the data provides an overview of different discursive elements. Grouping codes into clusters allows for the identification of specific discourse themes or dimensions. The connecting lines also show how codes interact and which codes frequently appear together. This allows for a detailed examination of the relationships between discursive elements, facilitating the interpretation and analysis of the discourse.

Document Map

The Document Map visualizes selected documents like a map. The positioning of the circles on the map is based on the similarity of the code assignments between the documents. Documents with similar code mappings are placed closer together, while those with different code mappings are placed further apart. Variable values from the documents can be used to determine similarity. Optionally, similar documents can be color-coded. Larger circles represent documents with more of the analyzed codes. The Document Map is a useful tool for visually grouping cases and can be used for typing or further investigation of the identified groups. The Document Map can be used in several ways in discourse analysis:

• Discourse group identification: By positioning documents on the map based on their code assignments, similar discourse groups can be identified. Documents with similar code assignments are placed closer together, indicating common discursive features.
• Recognition of discourse patterns: The visual representation of documents and their similarities on the map allows for the detection of patterns in discourse. Clusters of documents with similar codings may indicate common themes, arguments, or language patterns.
• Exploration of discourse dynamics: The use of connecting lines between codes on the map can reveal which codes overlap within documents. Thick connecting lines indicate frequent overlap and may suggest discursive relationships or connections.”
• Typification: The Document Map can serve as a basis for typology in discourse analysis. By grouping documents with similar code assignments, different discourse types can be identified and described”.

Profile Comparison Chart

The Profile Comparison Chart MAXQDA allows you to select multiple documents and compare the use of codes within those documents. This comparison allows you to identify differences or similarities in discourse between the selected documents. Below are some steps for using the Profile Comparison Chart:

• Document selection: Select the documents you want to compare. You can choose single documents or a group of documents. These documents should represent the discourse you want to analyze.
• Code selection: Select the codes you wish to compare in the selected documents. These can be specific themes, concepts or discursive elements that are of interest in the discourse.
• Create the comparison chart: Create the comparison graph in MAXQDA. The graph shows the occurrence of codes in individual paragraphs of the documents.
• Analysis of the chart: Analyze the comparison chart to identify differences or similarities in the discourse of the selected documents. Examine the assignment of codes in the paragraphs of the documents. Different patterns or variations in frequency may indicate differences in discourse, while similar patterns may indicate similarities in discourse.

Document Portrait

The Document Portrait feature in MAXQDA allows you to visually represent important features, themes, or characteristics of a document by visualizing the sequence of coding within that document. This feature allows you to identify relevant aspects of the discourse and analyze their weight in this particular document. Below are some steps for using the Document Portrait:

• Document Selection: Select the document for which you want to create a document portrait. The document selected should be representative of the discourse you are analyzing.
• Identify relevant features: Identify the codes that you want to visualize. These may be specific relevant features, themes or characteristics of the document, or other elements relevant to the discourse.
• Weighting of Features: The length of the segment is used as a weighting factor for the Document Portrait.
• Creation of the Document Portrait: Generate the Document Portrait in MAXQDA. The portrait visualizes the identified features and their weighting in the selected document. As a result, you obtain a visual representation of the sequence of coding performed within the document.
• Analysis of the Portrait: Analyze the Document Portrait to identify important features, themes, or characteristics of the document. This allows you to locate and understand relevant aspects of the discourse within a particular document.

The Codeline is a powerful tool in MAXQDA that allows you to visually represent the use of different codes within a document. By displaying the sequence of codes, you can see the flow and development of the discourse. With the Codeline, you can not only see which codes were used in specific sections of the document, but you can also track the progression of codings within a document. This allows you to identify crucial stages, turning points, or focal points in the discourse.The Codeline also allows you to analyze coded segments over time. You can examine specific codes and their occurrences or changes over time. This allows you to examine and interpret trends, patterns, or changes in the discourse more closely. The Codeline is therefore a valuable tool for considering the temporal progression and development of discourse in your analysis.By analyzing coded segments over time, you can gain a deeper understanding of the dynamics and context of the discourse, leading to more informed interpretations.

The Word Cloud is a powerful visualization tool in MAXQDA that helps you visually represent frequently occurring words or terms in the discourse. By looking at the size or weight of the words in the Word Cloud, you can quickly see which terms are particularly prevalent or significant in the discourse. By analyzing the Word Cloud, you can identify key terms in the discourse and examine their weight or frequency in relation to other terms. This allows you to identify and understand important themes, trends, or focuses in the discourse. In addition, you can use the Word Cloud to identify connections between different terms. If certain words occur frequently together or are used in similar contexts, you can identify associations or links in the discourse. The Word Cloud is thus a valuable tool for getting a quick and clear representation of the most common words or terms in the discourse. By analyzing the key terms and their weighting, you can gain important insights into the content and structure of the discourse and make a well-informed interpretation.

We offer a variety of free learning materials to help you get started with MAXQDA. Check out our Getting Started Guide to get a quick overview of MAXQDA and step-by-step instructions on setting up your software and creating your first project with your brand new QDA software. In addition, the free Literature Reviews Guide explains how to conduct a literature review with MAXQDA.

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Home » Discourse Analysis – Methods, Types and Examples

Discourse Analysis – Methods, Types and Examples

Table of Contents

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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Brodscholl, Per Christian. "Negotiating sustainability in the media: critical perspectives on the popularisation of environmental concerns." Thesis, Curtin University, 2003. http://hdl.handle.net/20.500.11937/2240.

Lillian, Donna L. "Canadian neo-conservative discourse a critical discourse analysis /." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/NQ66355.pdf.

Christianopoulos, Victor Steve. "A media discourse analysis." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B3014615X.

Seidlhofer, Barbara. "Discourse analysis for summarization." Thesis, University College London (University of London), 1991. http://discovery.ucl.ac.uk/10018780/.

Thornborrow, Joanna. "Discourse, power and ideology : some explorations in critical discourse analysis." Thesis, University of Strathclyde, 1991. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21500.

Campbell, Isaac. "Discourse Analysis of Sustainable Consumption." Thesis, Karlstad University, Faculty of Social and Life Sciences, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-340.

In the following C-Level Thesis, the geographically isolated consumer society that has evolved in the developed world is examined through discourse analysis. This research frames the issue of material consumption in a historical context and then interrogates the modern task of sustainability. Through review and analysis of current discourse in the sociopolitical field of sustainable consumption, this paper critically analyzes the development of modern consumer culture. The concept of ecological citizenship is presented and inspected as an effective strategy for the realization of sustainability and is viewed as a unifier of the many conflicting discourses on sustainable consumption. The dominant institutional discourse of ecological modernization is presented through a review of UK policy documents, and the opinions as well as alternative solutions touted by critics is noted. This paper finds that ideal of ecological citizenship has not yet been reached, but positive steps have been taken to achieve the goal of sustainability through curbing consumptive habits. In this presentation of sustainable consumption discourse it is important to recognize that there may be no absolute answer or right way to live on this planet, but rather, many ways which can, together, bring about a sustainable society.

Joty, Shafiq Rayhan. "Discourse analysis of asynchronous conversations." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45674.

Okiriguo, Wendy. "Discourse Analysis of Nigerian Feminism." Thesis, Southern Illinois University at Edwardsville, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10128866.

This study interprets the public perceptions of feminism and gender equality in Nigeria as reflected in the media. In recent times, the issue of gender equality has been subject to numerous debates in Nigeria. My interest in this issue stems from the increased awareness of feminism and a growing feminist movement in the country. This thesis details the popular opinions on feminism found on Nigerian blogs, online newspaper columns, social media and the likes. The purpose of this research was to (1) analyze feminism as a discourse in the Nigerian society (2) identify the existing gender issues (3) contribute to the growing body of transnational feminism. The findings reveal the dynamic interplay of gender and culture. The main discourses are centered on the relevance/irrelevance of feminism and the advocacy for the girl child rights. These findings have implications for the larger discourse regarding the correlation between culture and gender equality. Furthermore, findings indicate that issues concerning gender inequality is mostly linked with the cultural expectations of the particular society.

Rankoe, Matsheliso Xoliswa. "Exile identity : a discourse analysis." Master's thesis, University of Cape Town, 1999. http://hdl.handle.net/11427/13494.

Ivanov, Sergej. "Discourse Analysis in EFL Reading." Thesis, Malmö högskola, Lärarutbildningen (LUT), 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-31070.

Taranto, Gina Christine. "Discourse Adjectives /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2003. http://wwwlib.umi.com/cr/ucsd/fullcit?p3099909.

Brodscholl, Per Christian. "Negotiating sustainability in the media: critical perspectives on the popularisation of environmental concerns." Curtin University of Technology, Faculty of Media, Society and Culture, 2003. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=13600.

McCullough, Ryan Phillip. "Reconstructing poverty discourse." Huntington, WV : [Marshall University Libraries], 2005. http://www.marshall.edu/etd/descript.asp?ref=556.

McLean, Stacy Avril. "Negotiating identity in multilingual parliamentary discourses in the Western Cape: a discourse analysis." Thesis, University of the Western Cape, 2014. http://hdl.handle.net/11394/4282.

Munier, Opitz Bénédicte. "Les discours sur l'allaitement en France et en Allemagne : d'un geste privé à un acte public." Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCB208.

Choi, Jane Boyun. "A corpus-based discourse analysis of Korean discourse markers an analysis of spoken and written use /." Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1481658111&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

Evans, Rob. ""Learning discourse" : learning biographies, embedded speech and discoursal identity in students' talk." n.p, 2001. http://dart.open.ac.uk/abstracts/page.php?thesisid=109.

Murgia, Pamela. "Hama's statements: a discourse analysis approach." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664233.

Flobakk, Fride Røe. "Educational Neuroscience - A Critical Discourse Analysis." Thesis, Norges teknisk-naturvitenskapelige universitet, Pedagogisk institutt, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-13057.

Smith, Yancy W. "Discourse analysis and consolation in Philippians." Theological Research Exchange Network (TREN) Access this title online, 2003. http://www.tren.com.

Wong, So Fei. "Analysis of teachers' discourse on ijime /." Title page, contents and introduction only, 2001. http://web4.library.adelaide.edu.au/theses/09AR/09arw872.pdf.

Cheung, Wai-ling Sonia, and 張慧玲. "A contrastive discourse analysis of warnings." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B30409202.

Marks, Deborah. "Discourse analysis and education case conferences." Thesis, Manchester Metropolitan University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335397.

Badram, Dany. "Ideology through modality in discourse analysis." Thesis, University of Nottingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275961.

Tyrwhitt-Drake, Hugh. "A critique of critical discourse analysis." Thesis, University of Reading, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424028.

Hariki, Seiji. "Analysis of mathematical discourse : multiple perspectives." Thesis, University of Southampton, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315400.

Madders, S. "A discourse analysis of recovery stories." Thesis, University of Essex, 2018. http://repository.essex.ac.uk/22410/.

Donno, Julian. "American Progress - A Foucauldian Discourse Analysis." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-21695.

Yang, Wenhui. "A discourse analysis of trade negotiations." HKBU Institutional Repository, 2008. http://repository.hkbu.edu.hk/etd_ra/861.

Powers, Penny. "A discourse analysis of nursing diagnosis /." Thesis, Connect to this title online; UW restricted, 1994. http://hdl.handle.net/1773/7330.

Cheung, Wai-ling Sonia. "A contrastive discourse analysis of warnings /." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk:8888/cgi-bin/hkuto%5Ftoc%5Fpdf?B23424369.

MURGIA, PAMELA. "Hamas' statements. A discourse analysis approach." Doctoral thesis, Università degli Studi di Cagliari, 2018. http://hdl.handle.net/11584/255499.

Patterson, Natasha. "A womanist discourse analysis of the comedic discourse of Jackie "Moms" Mabley." [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0014282.

Bernard, Taryn. "Justificatory discourse of the perpetrator in TRC testimonies : a discourse-historical analysis." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/1571.

Mlotsa, Faith Busisiwe. "Learner involvement in discourse : a contextualised discourse analysis of undergraduate online discussions." Master's thesis, University of Cape Town, 2001. http://hdl.handle.net/11427/7881.

Jen, Clare Ching. "SARS discourse analysis technoscientific race-nation-gender formations in public health discourse /." College Park, Md.: University of Maryland, 2008. http://hdl.handle.net/1903/8798.

Li, Citing. "Chinese EFL learners' pragmatic and discourse transfer in the discourse of L2 requests." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43085763.

Nielsen, Barry. "Discourse analysis in Malachi 1:1-29." Theological Research Exchange Network (TREN), 1996. http://www.tren.com.

Burris, Jessica Margaret. "Finding Feminism in American Political Discourse : A Discourse Analysis of Post-Feminist Language." UNF Digital Commons, 2012. http://digitalcommons.unf.edu/etd/395.

Temple, Codruta. "Teaching and learning mathematical discourse in a Romanian classroom : a critical discourse analysis." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available, full text:, 2008. http://wwwlib.umi.com/cr/syr/main.

Franci, Lucrezia <1993&gt. "The coronavirus discourse: a corpus-assisted discourse analysis of Boris Johnson's institutional statements." Master's Degree Thesis, Università Ca' Foscari Venezia, 2021. http://hdl.handle.net/10579/20029.

Hardin, Pamela K. "Women, bodies, and self-surveillance : recovery from anorexia : a discourse of social analysis and an analysis regarding discourse /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/7366.

Buczek, Joshua David. "Cripple effects between discourse and event /." Diss., Online access via UMI:, 2006.

Proctor, M. "Discourse organization patterns and their signals : A clause relational approach to the analysis of written discourse." Thesis, University of Exeter, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380344.

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‘The Age of Magical Overthinking’ tries to pinpoint our mental health crisis

Amanda montell casts a wide net in her new essay collection. maybe too wide..

Every generation has its own crisis, the linguist and podcaster Amanda Montell writes. In the 1960s and ’70s, young Americans organized against “physical tyrannies” such as voter suppression and workplace discrimination. But times have changed.

The 21st century brought a shift in our attention from external threats to internal ones, Montell says. Rates of anxiety and depression among U.S. teens and adults have spiked. Loneliness is a public health threat . We’re glued to our phones, alienated from loved ones and surrounded by misinformation.

People everywhere, Montell writes, are facing a crisis of the mind.

From this grim landscape emerges “ The Age of Magical Overthinking: Notes on Modern Irrationality ,” Montell’s third book and a sweeping look at mental health, behavioral science, misinformation and online culture in the 2020s. In it, she argues that the ills of the internet era are best explained by looking back on humanity’s history, when our minds developed shortcuts to improve our odds of survival. Those shortcuts are called cognitive biases, and they may lead us to do strange things like fall for a conspiracy theory or accept mental health advice from an untrained influencer .

Montell leads us through an engaging roundup of “21st century derangement,” from celebrity worship to tradwife discourse , examining how cognitive biases may contribute. But by positioning her work as a response to America’s broad struggle with mental health, Montell promises more than she delivers. Rather than focusing on a tour of our shared cognitive glitches, she juggles meta-commentary on such vast topics as the modern mind and the internet, dropping balls along the way.

The book opens with an account of Montell’s struggles with anxiety and overwhelm, as well as the steps she took to feel better. “My most cinematic attempt at mental rehab involved picking herbs on a farm in Sicily under a light-pollution-free sky,” she writes.

Eventually, she had an aha moment: The same cognitive biases she encountered while researching toxic social groups for her second book, “ Cultish ,” could explain why the internet age felt like a “mass head trip.” Glutted with more information in a day than we can ever hope to process, we fall back on mental habits developed when humans were simpler creatures, Montell writes. For example, social media celebrity worship could be fueled by the “halo effect,” where we assume a person with one good quality (writing hit pop songs) has other good qualities (a perfectly tuned moral compass). Or perhaps we spend hours comparing ourselves with other people on Instagram because the “zero-sum bias” has convinced us that life is a game of winners and losers.

Montell backs up her connections in many instances with nods to evolutionary biology. For early humans, it made sense to attach ourselves to the strongest and most powerful, so now we glom onto Taylor Swift or Charli XCX. Resources like mates and status were limited in ancient human communities, Montell notes, so it’s natural that we view hot people on Instagram as immediate threats to our survival.

Montell finds examples of cognitive bias in internet culture flash points, such as the millennial obsession with New Age therapy-speak. Faced with big problems, such as anxiety or depression, our minds seek big explanations, such as childhood trauma or a scarcity mind-set, rather than examining all the smaller problems at play.

In other spots, she shares stories from her own life. In her late 20s, she struggled to end an abusive relationship, terrified that giving up meant she’d wasted years of her life — a classic “sunk cost fallacy.” Humans are social creatures, Montell notes, afraid of inviting scrutiny by admitting mistakes.

“My hope is for these chapters to make some sense of the senseless,” Montell says early on. “To crack open a window in our minds, and let a warm breeze in.” And indeed, in some moments, her sharp descriptions of behavioral foibles and her talent for cutting through doublespeak clear room for hope: Maybe noticing our warped thinking will make its effects less painful. Maybe our generational “crisis” is a story of not-enough-neurons encountering too-many-terabytes.

When confidence in Montell’s analysis wavers, it’s because the targets are too broad, the claims imprecise. For instance, we’re never quite sure of the shape of the national mental health crisis she repeatedly references. Early on, she draws a distinction between Americans’ current mental health struggles and 20th-century battles against bodily oppression. This neat separation doesn’t reflect reality — “The Age of Magical Overthinking” was published after Dobbs v. Jackson Women’s Health Organization and during ongoing fights for voter access, health care and the right to protest. It also doesn’t reflect what science has shown about illnesses like depression, which are often tied up with a person’s physical and political well-being. Ultimately, we’re left with the sense that Montell’s crisis of the mind begins and ends with the vague feelings of anxiety and dread many people feel after scrolling on social media apps.

Montell implies that the breakdown of Americans’ mental health began after 2000, brought on by internet access and introspection. Conflating “the internet” with social media, she draws loose connections between online scrolling and mental turmoil, making no reference to the complicated science around how social media use affects our brains. Some studies have found bumps in anxiety and depression associated with social media use, but more recent meta-analyses call their methods and findings into question . To date, researchers have found no consistent causal link between spending time on social apps and experiencing symptoms of depression and anxiety.

Of course, future research may uncover new ways to measure how social media use or other online activities affect the mental health of different populations. Perhaps we should rely on a different measure altogether, like qualitative research into young people and their families. Rather than critique the existing science or offer an alternative lens, Montell picks two studies that support her thesis and hand-waves at the dire state of things.

Finally, although Montell says cognitive biases affect everyone, she aims her jabs at the safest of targets: “Disney adults,” “male girlbosses,” “Facebook-addicted Karens.” Readers hoping for fresh or counterintuitive takes on internet culture — and its heroes and villains — may walk away disappointed.

Montell says from the jump that her analysis of 2020s malaise is “not a system of thought,” likening her work instead to a Buddhist koan — meant to be pondered, not understood. That’s fine, and “The Age of Magical Overthinking” ultimately features interesting topics, fun research and vivid stories. But in Montell’s effort to critique the spirit of our times, she asks imprecise questions and offers unsatisfactory answers.

Tatum Hunter is a consumer technology reporter at The Washington Post based in San Francisco. Her work focuses on health, privacy and relationships in the internet era.

The Age of Magical Overthinking

Notes on Modern Irrationality

By Amanda Montell

Atria/One Signal. 272 pp. $28.

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