“The oldest and most natural form of sense making” are stories or narratives (Jonansses & Hernandez-Serrano, 2002, p. 66). Stories are how we make sense of our experiences, how we communicate with others, and through which we understand the world around us. Stories, also called “narratives” have become a popular source of data in qualitative research. The key to this type of qualitative research is the use of stories as data, and more spefically, first-person accounts of experience told in story form having a beginning, middle, and end. Other terms for these stories of experience are biography, life history, oral history, autoethnography, and autobiography.
First-person accounts of experience constitute the narrative “text” of this research approach. Whether the account is in the form autobiography, life history, interview, journal letters, or other materials, the text is analyzed for the meaning it has for its author.
As with other forms of qualitative research, narrative research makes use of various methodological approaches to analyzing stories. Each approach examines, in some ways, how the story is constructed, what linguistic tools are used, and the cultural context of the story. For example, a biographical approach can seek to understand the influece of gender, race, family of origin, life events, turning point experiences, and/or other persons in the participants’ life. As well, a psychological approach concentrates more on the personal, including thoughts and motivations. A linguistic approach, or discourse analysis, focuses on the language of the story or the spoken text, and and also attends to the speaker’s intonation, pitch, and pauses.
This page features narrative analysis tools, resources, and examples to help you analyze your narrative data. Below is a brief outline differentiating four types of narrative analysis (adapted from Cresswell, 2009 and Merriam, 2009):
Thematic analysis in its simplest form is a categorizing strategy for qualitative data. Researchers review their data, make notes and begin to sort it into categories. Styled as a data analytic strategy, it helps researchers move their analysis from a broad reading of the data towards discovering patterns and developing themes. While researchers debate whether thematic analysis is a complete “method” per se, it is a process that can be used with many kinds of qualitative data, and with many goals in mind. For that reason, thematic analysis is often implicitly and explicitly a part of other types of data analysis including discourse analysis, grounded theory, and case study.
You can download more information about the application of thematic analysis below:
Fereday, J. & MuirCochrane, E. (2006). Demonstrating rigor using thematic analysis: A hybrid approach of inductive and deductive Qualitative Methods, 5(1), 8092.
In this article, the authors demonstrate how they used thematic analysis to code qualitative data. In doing so, they combine inductive and deductive approaches to identity themes and interpret the data. Deductive data analysis is characterized as examining the general data into specific themes and is informally discussed as the ‘topdown’ approach. Inductive data analysis begins from more specific observations to broader generalizations and theories. A deductive approach usually begins with a hypothesis whereas an inductive approach explores new phenomena. Oftentimes the analysis of qualitative data can require both inductive and deductive thematic analysis. This article is especially helpful for exemplifying how to organize data, which steps to take during the coding process, and the ways in which utilizing thematic analysis can facilitate the interpretation of data. This approach is useful in narrative analysis because it synthesizes data while recognizing the contributions of the theoretical frameworks utilized, facilitating broader understanding of data collected.
Structural analysis focuses on the ways in which the narrative is conveyed by the speaker with particular emphasis given to the interaction between speaker and listener. In this form of analysis, the language that the speaker uses, the pauses in speech, discourse markers, and other similar structural aspects of speech are the focus. When utilizing this approach, oftentimes the narrative is divided into stanzas and each stanza is analyzed by itself and also in the way in which it connects to the other pieces of the narrative.
You can download more information about the application of structural analysis below:
Dialogical analysis is an interpretative methodology which closely analyzes spoken or written utterances or actions for their embedded communicative significance. Although dialogical analysis tends to focus on discourse, it is distinct from discourse analysis and conversation analysis because its focus goes beyond the question of how people speak and what they achieve by speaking. Dialogical analysis uses dialogue as a metaphor for understanding phenomena beyond communication itself, such as the self, internal dialogues, self-talk, misunderstandings, trust and distrust, the production of knowledge, and relations between groups in society.
You can download more information about the application of dialogical analysis below:
Visual analysis seeks to understand how words and images convey meaning; subsequently exploring the visual message.
The researcher is offering their analysis of the visual document in a manner that is clear, concise, and informative. Visual analysis is not describing the data, as the method explains the rhetorical strategies at work and the ways in which the document communicates visually.
You can download more information about the application of visual analysis below:
Goodwin, C. (2000). Practices of Seeing: Visual Analysis: An Ethnomethodological Approach. Handbook of Visual Analysis, 157-182.
In this article, the author demonstrates visual analysis through specific examples, so that the reader can understand how visual images produce meaningful details to the narrative, such as spatial and environmental setting, the progression of the narrative, and the visible depiction of the participants’ bodies . As a result, this approach enhances the narrative analysis by analyzing the nonverbal aspects to build a deeper, comprehensive understanding of the accounts researchers are analyzing.
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Information for this page has been has been adapted from these sources:
Merriam, Sharan B.Merriam, Sharan B. (2009) Qualitative research :a guide to design and implementation San Francisco, CA: Jossey-Bass.
Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches. Los Angeles, CA: Sage.