Qualitative analysis Research methodology.

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Presentation transcript:

Qualitative analysis Research methodology

Differences between qualitative and quantitative data Transcribing qualitative data: reproducing the original data (eg.: audio recording) verbatim as a word processed account. Additional contextual information must be included.

The nature of qualitative analysis Analyzing qualitative data without quantification (Quantified qualitative data can be analyzed in the same way as originally quantitative data). It is a non-numeric analysis. Its philosophical background is interpretivism and social constructivism. Quantitative analysis keeps closer to theory and research aims than quantitative analysis, because it is less mechanical and technical.

Revealing relationships Frequency (of a given phenomenon). Intensity or strentgh of the phenomenon. Structure: types and relationships between the types Patterns Causes Consequences (short term and long term)

Cross-case analysis Variable-oriented: Case-oriented General consequences Will not reveal all the factors about a given case Case-oriented Aims full understanding about a given case Will not lead to any generalizable result

Grounded theory method Purely inductive: builds on observations not on theories No preconceptions Steps: Frequencies per categories Integration of categories and their attributes Circumscribing the theory: limitations Writing out the theory

Semiotics Studies signs and symbols. Signs, symbols has no meaning on their own, it is created by the society and depends on the context. One symbol can bear multiple potential meanings. Further reading: American Journal of Semiotics; Punctum; Lawes R. (2018) Science and semiotics: What’s the relationship? International Journal of Market Research. 60(6):573-588. doi:10.1177/1470785318787944.

Conversational analysis Analysing human conversations. Nuances of the conversations has important meanings.

Coding The basic technique in qualitative analysis Searching for categories (e.g. themes) and patterns occurring across the data set Sources and types of codes: Theory driven coding: a priory codes Data driven coding (open coding): Derived from data by the researcher Actual terms used by the participants The unit of analysis is a theme or notion One unit can get more than one codes Can be used for quantification, too The ultimate aim of coding is understanding

Aids you can use in qualitative analysis Memos or summaries: Progress summaries Transcript summaries Document summaries Self-memos Research notebook The envelope method Concept-mapping

An example of a concept-map Source: Babbie 2016