Qualitative Methods

Analyzing Qualitative Data

Reading, Rereading, and Coding

After organizing your data, the next step is to become intimately familiar with it. This is accomplished by reading and rereading your entire data set several times. As you go through the process of reading and rereading, you will begin to notice similarities and consistencies your data. With each reading, you may also notice that different aspects of the data hold your attention--that is you see more ideas and patterns with each read through. You may have just had a conversation with a colleague, read a journal article or had an illuminating experience that has enabled you to see something more in your data that suddenly seems to be a fundamental pattern throughout your observations. This kind of realization is why rereading is so important. Analytic clarity and insight come only after time has been taken to reread and rethink through the data from a variety of prespectives.

Open Coding

During the rereading process, researchers will identify possible themes and patterns in the data, often writing them in the margins of their fieldnotes or interviews. This process is called open coding. At this point, the researcher is open to whatever appears from within the data. This is a somewhat unstructured process of initially noting similarities, consistencies, and possible interpretations that occur while becoming increasingly familiar with the data. It is important to be “open” at this point to all potential insights that occur as you immerse yourself in your data.

Example of Open Coding

Open coding helps you understand the “big picture” of your data. It helps you understand the breathe and depth of your data and the sociological answers it contains. Once you have achieved this level of immersion and familiarity, you can chose how to focus your analysis. If your data contains frequent examples of racial discrimination, then that would make a strong focus for your. Of, if your data contains only a few references to gender discrimination, even if they are great examples, that would not make a good choice for your focus. Some aspects of your data will seem more important or more interesting to you. Othertimes, everything will seem important and you will be at a loss for choosing a focus.

As you read through your data and open coding notes, ask yourself what is the most interesting, novel, or compelling aspect of your interviews, setting or documents? Were there things that surprised you? worried you? sickened you? scared you? You might also think of your potential reader--what might they find the most insightful in your data? What does your data have to teach other social scientists?

Once you are comfortable with your level of familiarity with your data and you have reviewed your open coding notations, you are ready to choose an analytic focus for your paper. With this focus in mind, the researcher returns to the data for a final focused coding session.

Focused Coding

In this process, each occurrence of the central theme and its subthemes are marked and labeled within the data. Then all the examples of each theme or subtheme are put together. Most researchers accomplish this electronically, creating separate document files for each theme. Though some do this with scissors, cutting hard copies of their data into strips and sorting them into thematic piles.