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Large textual corpora are available for some languages.
The information is distributed within database tables in large textual attributes with a free structure.
For comparative politics scholars who are often interestedin non-English and possibly multilingual textual datasets, theseadvances may be difficult to access.
Here, the textual datasets are mainly used for calculating the text-based similarity scores between entities for controlling the quiz difficulty levels.
A thematic analysis of the textual dataset was then carried out.
After transcription, the textual dataset was initially perused to conceptualise the overarching themes that existed within the transcripts at a high-level.
Machine learning here allows injecting knowledge contained in curated databases in the textual dataset, to quickly obtain a view of the functional concepts dealt with.
Audio recordings of the discussions were transcribed verbatim and thematic analysis of the textual dataset was carried out by two members of the research team.
Nvivo is a software for textual analysis of large qualitative datasets.
For large datasets, however, converting textual descriptions into a computer-readable format by human interaction is a tedious task.
Gaillard, F. et al. Quality Control of Large Argo Datasets.
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