A multiscale approach to network event identification using geolocated twitter data

Authors:
Chao Yang;Ian Jensen;Paul Rosen
Affiliations:
University of Utah, Salt Lake City, USA 84112;University of Utah, Salt Lake City, USA 84112;University of Utah, Salt Lake City, USA 84112
Venue:
Computing
Year:
2014

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Abstract

The large volume of data associated with social networks hinders the unaided user from interpreting network content in real time. This problem is compounded by the fact that there are limited tools available for enabling robust visual social network exploration. We present a network activity visualization using a novel aggregation glyph called the clyph. The clyph intuitively combines spatial, temporal, and quantity data about multiple network events. We also present several case studies where major network events were easily identified using clyphs, establishing them as a powerful aid for network users and owners.