Thematic Analysis: A Key Tool for Qualitative Research in Media Studies

Thematic Analysis: A Key Tool for Qualitative Research in Media Studies

Thematic Analysis: A Key Tool for Qualitative Research in Media Studies

Thematic analysis is a widely used technique in qualitative research, particularly in media and communication studies. It is a systematic method for organizing qualitative information by identifying patterns, topics, themes, and codes. The purpose of thematic analysis is to interpret and report meaningful patterns in the data. One of its strengths lies in its flexibility, which allows researchers to adopt diverse interpretative approaches. A theme captures significant aspects of the data in relation to the research question and represents patterned meanings within the data set.

As noted by Braun & Clarke (2013), thematic analysis is especially suitable for understanding experiences, thoughts, and behaviors across data sets. It provides researchers with a broad and open analytic position, accommodating a range of theoretical interpretations.

Types of Theme Identification Processes

  1. Inductive Thematic Analysis
    In this approach, themes emerge organically from the data, without prior expectations or theoretical frameworks. Researchers use this method to explore new phenomena.
  2. Deductive Thematic Analysis
    This approach involves applying a pre-existing coding frame to the data. Researchers use it to test existing theories by fitting data into established frameworks.

The Six Phases of Thematic Analysis

According to Braun & Clarke (2013), the thematic analysis process comprises six key phases:

Phase 1: Familiarising with the Data

Familiarisation involves immersing oneself in the data by reading and re-reading the textual data set and making observational notes. This phase helps researchers generate basic and analytical ideas. Riessman (1993) also emphasizes transcription as a crucial aspect of familiarisation.

Phase 2: Generating Initial Codes

Coding is the process of categorizing data into meaningful units. Codes can be simple labels or more complex categories, such as metaphors (Miles & Huberman, 1994).

  • Descriptive Coding: Assigns short labels to data segments, identifying topics.
  • Pattern Coding: Identifies relationships and patterns across data segments.

Phase 3: Searching for Themes

After generating codes, researchers analyze and group related codes into potential themes. Braun & Clarke describe this as a process of shifting the focus to broader patterns rather than individual codes. Theme identification can be categorized as:

  • Semantic Themes: Focus on explicit meanings within the data.
  • Latent Themes: Go beyond explicit meanings to explore underlying ideas.

Phase 4: Reviewing Themes

This phase involves refining, reshaping, or rejecting themes to ensure coherence with the research questions and data. Patton (2002) suggests two levels of theme review:

  • Internal Homogeneity: Ensures coded data extracts within a theme are coherent.
  • External Homogeneity: Ensures clear differentiation between themes.

Phase 5: Defining and Naming Themes

In this phase, researchers refine themes and identify their essence by organizing data extracts into coherent narratives. Sub-themes, if present, are also identified to create a comprehensive account of the data.

Phase 6: Producing the Report

The final phase involves writing a report that integrates the themes into a coherent narrative, addressing the research questions. Each theme and sub-theme is described with supporting data to substantiate its relevance.

Practical Tips for Thematic Analysis

  • Read and re-read the data to identify potential patterns.
  • Start coding line by line and then collapse related codes into single categories.
  • Focus on commonalities, differences, and recurring patterns within the data.
  • Align themes with research questions to create meaningful narratives.

References

  1. Braun, V., & Clarke, V. (2013). Successful Qualitative Research: A Practical Guide for Beginners. London, UK: SAGE.
  2. Riessman, C. K. (1993). Doing Narrative Analysis. Narrative Analysis. London, UK: SAGE.
  3. Miles, M. B., & Huberman, A. M. (1994). Qualitative Data Analysis: An Expanded Sourcebook (2nd ed.). Thousand Oaks, CA: SAGE.
  4. Saldaña, J. (2015). The Coding Manual for Qualitative Researchers. Thousand Oaks, CA: SAGE.
  5. Patton, M. Q. (2002). Qualitative Research and Evaluation Methods. London, UK: SAGE.

Author: Prem Chand Yadava

Read more…