The semantics of clustering: analysis of user-generated spatializations of text documents

TitleThe semantics of clustering: analysis of user-generated spatializations of text documents
Publication TypeConference Paper
Year of Publication2012
AuthorsEndert, A, Fox, S, Maiti, D, Leman, S, North, C
Conference NameProceedings of the International Working Conference on Advanced Visual Interfaces
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-1287-5
Keywordsclustering, text analytics, Visual Analytics, visualization
Abstract

Analyzing complex textual datasets consists of identifying connections and relationships within the data based on users' intuition and domain expertise. In a spatial workspace, users can do so implicitly by spatially arranging documents into clusters to convey similarity or relationships. Algorithms exist that spatialize and cluster such information mathematically based on similarity metrics. However, analysts often find inconsistencies in these generated clusters based on their expertise. Therefore, to support sensemaking, layouts must be co-created by the user and the model. In this paper, we present the results of a study observing individual users performing a sensemaking task in a spatial workspace. We examine the users' interactions during their analytic process, and also the clusters the users manually created. We found that specific interactions can act as valuable indicators of important structure within a dataset. Further, we analyze and characterize the structure of the user-generated clusters to identify useful metrics to guide future algorithms. Through a deeper understanding of how users spatially cluster information, we can inform the design of interactive algorithms to generate more meaningful spatializations for text analysis tasks, to better respond to user interactions during the analytics process, and ultimately to allow analysts to more rapidly gain insight.

URLhttp://doi.acm.org/10.1145/2254556.2254660
DOI10.1145/2254556.2254660
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