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Abstract: Among the knowledge elicitation techniques card sorting is notable for its simplicity of use, its focus on subjects' terminology (rather than that of external experts) and its ability to elicit semi-tacit knowledge. Card sorting involves categorizing a set of pictures, objects or labelled cards into distinct groups using a single criterion. This paper focuses on the challenges associated with analyzing the data that result from card sorts, especially when large data sets are generated. Traditional semantic analysis methods that require direct researcher interpretation of elicited linguistic terms are distinguished from methods that are purely syntactic, and hence can be automated. Each paper within this special issue is summarized and its contribution to card sorting in general, and data analysis in particular, is highlighted. The set of novel computational techniques presented in several of the papers in this issue is examined. The paper concludes by noting that even large-scale data sets can be meaningfully analysed by combining well-known interpretative methods with the new computational approaches presented within this special issue.
Fincher et al. (2005) studied this question.