Event Detection and Visualization for Social Text Streams
Wednesday, March 28, 2007
Qiankun Zhao and Prasenjit MitraIn this paper, we propose to detect events from social text streams by exploring the content as well as the temporal, and social dimensions. We define the term event in the social text streams(e.g., blogs, emails, and Usenets) as a set of relations between social actors on a specific topic over a certain time period. We represent social text streams as multi-graphs, where each node represents a social actor and each edge represents a piece of text communication that connects two actors. The content and temporal associations within each text piece are embedded in the corresponding edge. Then, events are detected by combining text-based clustering, temporal segmentation, and graph cuts of social networks. Moreover, we provide a multi-dimensional visualization tool that visualizes the relations between different events along the three different dimensions. Experiments conducted with the Enron email dataset1 show the advantages of exploring the social and temporal dimensions along with content, and the usefulness of the visualization tool.
Short Paper
posted by ICWSM at 10:23 AM
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