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A multiscale approach to network event identification using geolocated twitter data

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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.

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Acknowledgments

This work was funded in part by DOE NETL and NSF CDI-0835821.

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Authors and Affiliations

  1. University of Utah, 72 S. Central Campus Dr., RM 3750, Salt Lake City, 84112, UT, USA

    Chao Yang, Ian Jensen & Paul Rosen

Authors
  1. Chao Yang
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  2. Ian Jensen
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  3. Paul Rosen
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Corresponding author

Correspondence to Chao Yang.

Additional information

First IMC Workshop on Internet Visualization (WIV 2012), November 13, 2012, Boston, MA, USA.

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Yang, C., Jensen, I. & Rosen, P. A multiscale approach to network event identification using geolocated twitter data. Computing 96, 3–13 (2014). https://doi.org/10.1007/s00607-013-0285-5

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  • DOI: https://doi.org/10.1007/s00607-013-0285-5

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