Event detection in blogs using temporal random indexing

  • Authors:

  • David Jurgens;Keith Stevens

  • Affiliations:

  • University of California, Los Angeles, CA;University of California, Los Angeles, CA

  • Venue:
  • eETTs '09 Proceedings of the Workshop on Events in Emerging Text Types
  • Year:
  • 2009

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Abstract

Automatic event detection aims to identify novel, interesting topics as they are published online. While existing algorithms for event detection have focused on newswire releases, we examine how event detection can work on less structured corpora of blogs. The proliferation of blogs and other forms of self-published media have given rise to an ever-growing corpus of news, commentary and opinion texts. Blogs offer a major advantage for event detection as their content may be rapidly updated. However, blogs texts also pose a significant challenge in that the described events may be less easy to detect given the variety of topics, writing styles and possible author biases. We propose a new way of detecting events in this media by looking for changes in word semantics. We first outline a new algorithm that makes use of a temporally-annotated semantic space for tracking how words change semantics. Then we demonstrate how identified changes could be used to detect new events and their associated blog entries.