Textual analysis is a research methodology that involves exploring written text as empirical data. Scholars explore both the content and structure of texts, and attempt to discern key themes and statistics emergent from them.
This method of research is used in various academic disciplines, including cultural studies, literature, bilical studies, anthropology, sociology, and others (Dearing, 2022; McKee, 2003).
This method of analysis involves breaking down a text into its constituent parts for close reading and making inferences about its context, underlying themes, and the intentions of its author.
Textual Analysis Definition
Alan McKee is one of the preeminent scholars of textual analysis. He provides a clear and approachable definition in his book Textual Analysis: A Beginner’s Guide (2003) where he writes:
“When we perform textual analysis on a text we make an educated guess at some of the most likely interpretations that might be made of the text […] in order to try and obtain a sense of the ways in which, in particular cultures at particular times, people make sense of the world around them.”
A key insight worth extracting from this definition is that textual analysis can reveal what cultural groups value, how they create meaning, and how they interpret reality.
This is invaluable in situations where scholars are seeking to more deeply understand cultural groups and civilizations – both past and present (Metoyer et al., 2018).
As such, it may be beneficial for a range of different types of studies, such as:
- Studies of Historical Texts: A study of how certain concepts are framed, described, and approached in historical texts, such as the Bible.
- Studies of Industry Reports: A study of how industry reports frame and discuss concepts such as environmental and social responsibility.
- Studies of Literature: A study of how a particular text or group of texts within a genre define and frame concepts. For example, you could explore how great American literature mythologizes the concept of the ‘The American Dream’.
- Studies of Speeches: A study of how certain politicians position national identities in their appeals for votes.
- Studies of Newspapers: A study of the biases within newspapers toward or against certain groups of people.
- Etc. (For more, see: Dearing, 2022)
McKee uses the term ‘textual analysis’ to also refer to text types that are not just written, but multimodal. For a dive into the analysis of multimodal texts, I recommend my article on content analysis, where I explore the study of texts like television advertisements and movies in detail.
Features of a Textual Analysis
When conducting a textual analysis, you’ll need to consider a range of factors within the text that are worthy of close examination to infer meaning. Features worthy of considering include:
- Content: What is being said or conveyed in the text, including explicit and implicit meanings, themes, or ideas.
- Context: When and where the text was created, the culture and society it reflects, and the circumstances surrounding its creation and distribution.
- Audience: Who the text is intended for, how it’s received, and the effect it has on its audience.
- Authorship: Who created the text, their background and perspectives, and how these might influence the text.
- Form and structure: The layout, sequence, and organization of the text and how these elements contribute to its meanings (Metoyer et al., 2018).
Textual Analysis Coding Methods
The above features may be examined through quantitative or qualitative research designs, or a mixed-methods angle.
1. Quantitative Approaches
You could analyze several of the above features, namely, content, form, and structure, from a quantitative perspective using computational linguistics and natural language processing (NLP) analysis.
From this approach, you would use algorithms to extract useful information or insights about frequency of word and phrase usage, etc. This can include techniques like sentiment analysis, topic modeling, named entity recognition, and more.
2. Qualitative Approaches
In many ways, textual analysis lends itself best to qualitative analysis. When identifying words and phrases, you’re also going to want to look at the surrounding context and possibly cultural interpretations of what is going on (Mayring, 2015).
Generally, humans are far more perceptive at teasing out these contextual factors than machines (although, AI is giving us a run for our money).
One qualitative approach to textual analysis that I regularly use is inductive coding, a step-by-step methodology that can help you extract themes from texts. If you’re interested in using this step-by-step method, read my guide on inductive coding here.
Textual Analysis Examples
Title: “Discourses on Gender, Patriarchy and Resolution 1325: A Textual Analysis of UN Documents”
Author: Nadine Puechguirbal
APA Citation: Puechguirbal, N. (2010). Discourses on Gender, Patriarchy and Resolution 1325: A Textual Analysis of UN Documents, International Peacekeeping, 17(2): 172-187. doi: 10.1080/13533311003625068
Summary: The article discusses the language used in UN documents related to peace operations and analyzes how it perpetuates stereotypical portrayals of women as vulnerable individuals. The author argues that this language removes women’s agency and keeps them in a subordinate position as victims, instead of recognizing them as active participants and agents of change in post-conflict environments. Despite the adoption of UN Security Council Resolution 1325, which aims to address the role of women in peace and security, the author suggests that the UN’s male-dominated power structure remains unchallenged, and gender mainstreaming is often presented as a non-political activity.
Title: “Racism and the Media: A Textual Analysis”
Author: Kassia E. Kulaszewicz
APA Citation: Kulaszewicz, K. E. (2015). Racism and the Media: A Textual Analysis. Dissertation. Retrieved from: https://sophia.stkate.edu/msw_papers/477
Summary: This study delves into the significant role media plays in fostering explicit racial bias. Using Bandura’s Learning Theory, it investigates how media content influences our beliefs through ‘observational learning’. Conducting a textual analysis, it finds differences in representation of black and white people, stereotyping of black people, and ostensibly micro-aggressions toward black people. The research highlights how media often criminalizes Black men, portraying them as violent, while justifying or supporting the actions of White officers, regardless of their potential criminality. The study concludes that news media likely continues to reinforce racism, whether consciously or unconsciously.
Title: “On the metaphorical nature of intellectual capital: a textual analysis”
Author: Daniel Andriessen
APA Citation: Andriessen, D. (2006). On the metaphorical nature of intellectual capital: a textual analysis. Journal of Intellectual capital, 7(1), 93-110.
Summary: This article delves into the metaphorical underpinnings of intellectual capital (IC) and knowledge management, examining how knowledge is conceptualized through metaphors. The researchers employed a textual analysis methodology, scrutinizing key texts in the field to identify prevalent metaphors. They found that over 95% of statements about knowledge are metaphor-based, with “knowledge as a resource” and “knowledge as capital” being the most dominant. This study demonstrates how textual analysis helps us to understand current understandings and ways of speaking about a topic.
Title: “Race in Rhetoric: A Textual Analysis of Barack Obama’s Campaign Discourse Regarding His Race”
Author: Andrea Dawn Andrews
APA Citation: Andrew, A. D. (2011) Race in Rhetoric: A Textual Analysis of Barack Obama’s Campaign Discourse Regarding His Race. Undergraduate Honors Thesis Collection. 120. https://digitalcommons.butler.edu/ugtheses/120
This undergraduate honors thesis is a textual analysis of Barack Obama’s speeches that explores how Obama frames the concept of race. The student’s capstone project found that Obama tended to frame racial inequality as something that could be overcome, and that this was a positive and uplifting project. Here, the student breaks-down times when Obama utilizes the concept of race in his speeches, and examines the surrounding content to see the connotations associated with race and race-relations embedded in the text. Here, we see a decidedly qualitative approach to textual analysis which can deliver contextualized and in-depth insights.
Sub-Types of Textual Analysis
While above I have focused on a generalized textual analysis approach, a range of sub-types and offshoots have emerged that focus on specific concepts, often within their own specific theoretical paradigms. Each are outlined below, and where I’ve got a guide, I’ve linked to it in blue:
- Content Analysis: Content analysis is similar to textual analysis, and I would consider it a type of textual analysis, where it’s got a broader understanding of the term ‘text’. In this type, a text is any type of ‘content’, and could be multimodal in nature, such as television advertisements, movies, posters, and so forth. Content analysis can be both qualitative and quantitative, depending on whether it focuses more on the meaning of the content or the frequency of certain words or concepts (Chung & Pennebaker, 2018).
- Discourse Analysis: Emergent specifically from critical and postmodern/ poststructural theories, discourse analysis focuses closely on the use of language within a social context, with the goal of revealing how repeated framing of terms and concepts has the effect of shaping how cultures understand social categories. It considers how texts interact with and shape social norms, power dynamics, ideologies, etc. For example, it might examine how gender is socially constructed as a distinct social category through Disney films. It may also be called ‘critical discourse analysis’.
- Narrative Analysis: This approach is used for analyzing stories and narratives within text. It looks at elements like plot, characters, themes, and the sequence of events to understand how narratives construct meaning.
- Frame Analysis: This approach looks at how events, ideas, and themes are presented or “framed” within a text. It explores how these frames can shape our understanding of the information being presented. While similar to discourse analysis, a frame analysis tends to be less associated with the loaded concept of ‘discourse’ that exists specifically within postmodern paradigms (Smith, 2017).
- Semiotic Analysis: This approach studies signs and symbols, both visual and textual, and could be a good compliment to a content analysis, as it provides the language and understandings necessary to describe how signs make meaning in cultural contexts that we might find with the fields of semantics and pragmatics. It’s based on the theory of semiotics, which is concerned with how meaning is created and communicated through signs and symbols.
- Computational Textual Analysis: In the context of data science or artificial intelligence, this type of analysis involves using algorithms to process large amounts of text. Techniques can include topic modeling, sentiment analysis, word frequency analysis, and others. While being extremely useful for a quantitative analysis of a large dataset of text, it falls short in its ability to provide deep contextualized understandings of words-in-context.
Each of these methods has its strengths and weaknesses, and the choice of method depends on the research question, the type of text being analyzed, and the broader context of the research.
Strengths and Weaknesses of Textual Analysis
|Strengths of Textual Analysis||Weaknesses of Textual Analysis|
|Helps to develop detailed understandings of how meaning is produced in language (McKee, 2003).||Textual analyses often focus too much on written text and fail to account for the various social cues we receive through nonverbal communication events.|
|Allows anthropologists, sociologists, cultural theorists, and historians to gather a set of texts from a specific moment in time to gather insights of how cultures have created within their specific historical contexts (Chung & Pennebaker, 2018).||Qualitative textual analyses, which in my opinion render richest results, also have higher likelihood of being influenced by researcher bias – conscious or unconscious. Scholars need clear reliability and validity mechanisms to hedge against this (Smith, 2017).|
|Provides a means and methodological language for extracting meaning from texts, which is far more thoroughly fleshed-out than many other approaches, which often engage in textual coding with arguably less methodological rigor (i.e coding of semi-structured interviews).||Quantitative textual analyses, such as through use of AI and computer programs, often fail to extract nuanced cultural and contextual readings, which can only be achieved by a rich quantitative approach.|
|Can help to bring to the fore meanings sedimented within texts that we take for granted and fail to critique. By using sentiment analysis whenever a term is used, for example, we can extract how concepts are associated with negative and positive feelings within cultural texts.||Textual analysis alone is often seen as a poor form of empirical research, as there is an expectation that we don’t just infer meanings form texts, but engage with actual readers of those texts to see how they infer meanings – as it’s how people make meaning of texts, rather than the texts themselves, that can reveal how texts give life to ideas.|
When writing your methodology for your textual analysis, make sure to define not only what textual analysis is, but (if applicable) the type of textual analysis, the features of the text you’re analyzing, and the ways you will code the data. It’s also worth actively reflecting on the potential weaknesses of a textual analysis approach, but also explaining why, despite those weaknesses, you believe this to be the most appropriate methodology for your study.
Chung, C. K., & Pennebaker, J. W. (2018). Textual analysis. In Measurement in social psychology (pp. 153-173). Routledge.
Dearing, V. A. (2022). Manual of textual analysis. Univ of California Press.
McKee, A. (2003). Textual analysis: A beginner’s guide. Textual analysis, 1-160.
Mayring, P. (2015). Qualitative content analysis: Theoretical background and procedures. Approaches to qualitative research in mathematics education: Examples of methodology and methods, 365-380. doi: https://doi.org/10.1007/978-94-017-9181-6_13
Metoyer, R., Zhi, Q., Janczuk, B., & Scheirer, W. (2018, March). Coupling story to visualization: Using textual analysis as a bridge between data and interpretation. In 23rd International Conference on Intelligent User Interfaces (pp. 503-507). doi: https://doi.org/10.1145/3172944.3173007
Smith, J. A. (2017). Textual analysis. The international encyclopedia of communication research methods, 1-7.
Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]