4.2.2 Qualitative analysis
Qualitative analysis examines the research topic through the description and interpretation of our data, frequently, with the goal of developing new concepts and theories. For this reason, qualitative research tends to generate theories inductively rather than testing them deductively as we saw with the quantitative approach. Qualitative theories are said to be grounded in data. This ‘grounded theory’ is a process of theory formation in which theory emerges from the intertwinement of the data collection and analysis. For this reason, the qualitative processes of data collection, wrangling and analysis are not sequential, like in quantitative research, but intertwined. The focused nature of qualitative research together with the lack of representative samples of the studied populations or objects originate results that are valid for the analysed case with few if any generalisation claims. Some of the most commonly used qualitative analysis techniques include:
- Narrative analysis repurposes stories as data to make an interpretation about the context in which they are produced or constructed.
- Discourse analysis is related to the study of the usage of language within data (texts), which are investigated in a structured and systematic way to reveal the socially constructed and constructive nature of language.
- Content Analysis dispels the traditional and strict division between words and numbers as delimiters of qualitative and quantitative approaches. This technique is used to count the number of words and/or codes contained in our data and then interpret the meaning of those frequencies within the context of our research question. Digital data and tools, such as text mining, have improved both the scope and the capacity to meaningful analyse large corpora through content analysis.