Computer-assisted Content Analysis of Twitter Data

Jessica Einspänner, Mark Dang-Anh & Caja Thimm

Content analysis provides a useful and multifaceted, methodological framework
for Twitter analysis. CAQDAS tools support the structuring of textual data by
enabling categorising and coding. Depending on the research objective, it may
be appropriate to choose a mixed-methods approach that combines quantitative
and qualitative elements of analysis and plays out their respective advantages
to the greatest possible extent while minimising their shortcomings.

In this chapter, we will discuss CAQDAS speech act analysis of tweets as an example
of software-assisted content analysis. We start with some elementary thoughts
on the challenges of the collection and evaluation of Twitter data before we
give a brief description of the potentials and limitations of using the software
QDA Miner (as one typical example for possible analysis programmes). Our
focus will lie on analytical features that can be particularly helpful in speech
act analysis of tweets.

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