How to Code and Write an Analysis from Qualitative Interview Transcriptions

Qualitative interviews can provide a wealth of insights, but they also come with a significant challenge: organizing and analyzing the data. This article delves into the step-by-step process of coding qualitative interview transcriptions and writing a comprehensive analysis. Whether you are a researcher, a marketer, or a journalist, these guidelines will help you structure your work more efficiently and effectively.

Starting with a Research Question

A clear research question is crucial when working with qualitative data. It helps you focus on what you need to find out, ensuring that you don't get lost in a sea of potential information. For instance, your research question could be:

In which parts of the world do people most frequently discuss climate change? In which parts of the week do people experience the highest levels of stress? In which parts of the body do people feel the most pain?

Having a specific question guides your coding process and ensures that your analysis is relevant and impactful.

Checking the Scope of Interest

Once you have a research question, it is essential to check the scope of your inquiry. This step ensures that your question is broad enough to capture valuable insights but specific enough to yield actionable results. A useful method is to identify the major themes in your source material. For example, if you are analyzing Trump's acceptance speech, you might find themes such as 'people', 'verbs of action', 'tangible content', 'emotional expressions', etc.

Organizing Your Raw Material

Before beginning the coding process, it's wise to organize your raw material. This involves separating the essential content from metadata. Keep the questions outside as metadata and the answers inside. For instance, keep the name of the interviewer and the interviewee separate from the transcribed responses. Avoid including page numbers, as they can distract you from the main content.

Coding - The Big Job

Coding can be a daunting task, but it is an essential step in the analysis process. The challenge often arises from the lack of productive solutions and cooperation among coders. Think of it as a team effort, where each person focuses on a specific aspect of the analysis, much like a group of professionals working together to achieve a common goal.

One approach to making the coding process more manageable is to use pre-existing codes or a pre-built topic structure. These structures help you recognize relevant themes and organize your analysis more systematically. For example, a built-in topic structure might include names of countries, cities, regions, and other relevant geographic information.

Developing Your Own Code

While using pre-existing codes is beneficial, you may occasionally need to develop your own codes. This is particularly true when your research question requires specific focus areas that are not covered by the pre-existing codes. To create your own code, follow these steps:

Research Question Focus: Ensure that your code can recognize the relevant themes related to your research question. For instance, if you are focusing on geography, your code should be able to identify key regions, countries, and cities. An example would be a code that categorizes responses based on geographical regions. Structuring Your Code: Organize your code hierarchically. This means that some elements will be parents, and others will be children. Create a structure that allows for a nested organization, similar to a family tree. An example would be a hierarchy like: Continent > Country > City > Topic.

Intersection Analysis

Once you have organized your codes, you can conduct intersection analysis to identify patterns and co-incident themes in your data. This method helps you compare and contrast different elements within your source material. For instance, if your research question intersects sports and specific countries, you can analyze quotes where these elements coincide.

An example of intersection analysis is when you find quotes related to soccer and Brazil. You can explore the co-incident references and delve into the 71 quotes where soccer and Brazil coincide. This approach will help you identify trends and patterns that emerge from your data.

Conclusion

Qualitative interviews provide rich insights, but they require careful organization and analysis. By following these steps, you can ensure that your data is coded effectively and your analysis is thorough. Whether you are working on a research project, a marketing campaign, or a journalistic investigation, the process outlined here will help you structure your work more efficiently and effectively.