To help you with the analysis of qualitative data, it is useful to produce an interview summary form or a focus group summary form which you complete as soon as possible after each interview or focus group has taken place. This includes practical details about the time and place, the participants, the duration of the interview or focus group, and details about the content and emerging themes. It is useful to complete these forms as soon as possible after the interview and attach them to your transcripts. The forms help to remind you about the contact and are useful when you come to analyse the data.

There are many different types of qualitative data analysis. The method you use will depend on your research topic, your personal preferences and the time, equipment and finances available to you. Also, qualitative data analysis is a very personal process, with few rigid rules and procedures.

Formats for analysis

However, to be able to analyse your data you must first of all produce it in a format that can be easily analysed. This might be a transcript from an interview or focus group, a series of written answers on an open-ended questionnaire, or field notes or memos written by the researcher. It is useful to write memos and notes as soon as you begin to collect data as these help to focus your mind and alert you to significant points which may be coming from the data. These memos and notes can be analysed along with your transcripts or questionnaires.

You can think of the different types of qualitative data analysis as positioned on a continuum. At the one end are the highly qualitative, reflective types of analysis, whereas on the other end are those which treat the qualitative data in a quantitative way, by counting and coding data.

For those at the highly qualitative end of the continuum, data analysis tends to be an on-going process, taking place throughout the data collection process. The researcher thinks about and reflects upon the emerging themes, adapting and changing the methods if required. For example, a researcher might conduct three interviews using an interview schedule she has developed beforehand. However, during the three interviews she finds that the participants are raising issues that she has not thought about previously. So she refines her interview schedule to include these issues for the next few interviews. This is data analysis. She has thought about what has been said, analysed the words and refined her schedule accordingly.

Thematic analysis

When data is analysed by theme, it is called thematic analysis. This type of analysis is highly inductive, that is, the themes emerge from the data and are not imposed upon it by the researcher. In this type of analysis, the data collection and analysis take place simultaneously. Even background reading can form part of the analysis process, especially if it can help to explain an emerging theme. Closely connected to thematic analysis is comparative analysis. Using this method, data from different people is compared and contrasted and the process continues until the researcher is satisfied that no new issues are arising. Comparative and thematic analyses are often used in the same project, with the researcher moving backwards and forwards between transcripts, memos, notes and the research literature.

Content analysis

For those types of analyses at the other end of the qualitative data continuum, the process is much more mechanical with the analysis being left until the data has been collected. Perhaps the most common method of doing this is to code by content. This is called content analysis. Using this method the researcher systematically works through each transcript assigning codes, which may be numbers or words, to specific characteristics within the text. The researcher may already have a list of categories or she may read through each transcript and let the categories emerge from the data. Some researchers may adopt both approaches. This type of analysis can be used for open-ended questions which have been added to questionnaires in large quantitative surveys, thus enabling the researcher to quantify the answers.

Discourse analysis

Falling in the middle of the qualitative analysis continuum is discourse analysis, which some researchers have named conversational analysis, although others would argue that the two are quite different. These methods look at patterns of speech, such as how people talk about a particular subject, what metaphors they use, how they take turns in conversation, and so on. These analysts see speech as a performance; it performs an action rather than describes a specific state of affairs or specific state of mind. Much of this analysis is intuitive and reflective, but it may also involve some form of counting, such as counting instances of turn-taking and their influence on the conversation and the way in which people speak to others.

Processing the data

1. You need to think about the data from the moment you start to collect the information.

2. You need to judge the value of your data, especially that which may come from dubious sources.

3. As your research progresses you need to interpret the data so that you, and others, can gain an understanding of what is going on.

4. Finally, you need to undertake the mechanical process of analysing the data.

It is possible to undertake the mechanical process using computing software which can save you a lot of time, although it may stop you becoming really familiar with the data. There are many dedicated qualitative analysis programs of various kinds available to social researchers that can be used for a variety of different tasks. For example, software could locate particular words or phrases; make lists of words and put them into alphabetical order; insert key words or comments; count occurrences of words or phrases or attach numeric codes. Some software will retrieve text, some will analyse text and some will help to build theory. Although a computer can undertake these mechanical processes, it cannot think about, judge or interpret qualitative data