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Data analysis

Depending on the objects(s) of study, the research questions and/or hypotheses and the chosen approach (descriptive, explorative or testing), you choose a specific research method. An analysis strategy will be part of this method.

After you have prepared your sources or collected your data, you can start your analysis. Often, certain tasks that are part of the analysis strategy can be supported by specific computer programs (tools). One of the main goals of this workbench is to describe the tools that are used most frequently for this purpose in our faculty and to refer you to various relevant reference manuals and/or practical introductions.

N.B. The information about analysis strategies is very concise; this workbench is not intended as a substitute for a methodology textbook, it's main aim is to point you to relevant tools that may support your analysis.

In this workbench the following analysis techniques are discussed, based on the type of data that are analysed:

• Textual data:
  • Basic text analysis
  • Qualitative analysis
  • Content analysis
  • Corpus analysis
  • Sentiment analysis
  • Text mining
  • Stylometry
• Conversation data: Conversation analysis
• Visual data: Analysis of visual data
• Structured data:
  • Statistical analysis
  • Network analysis
  • Spatial and temporal analysis

Other topics in this section: Introduction   Textual data   Conversation   Visual data   Structured data