TweetMotif: Exploratory Search and Topic Summarization for Twitter

Authors

  • Brendan O'Connor Carnegie Mellon University
  • Michel Krieger Meebo, Inc.
  • David Ahn Microsoft, Inc.

DOI:

https://doi.org/10.1609/icwsm.v4i1.14008

Keywords:

faceted search, summarization, clustering, microblogs, information retrieval, exploratory search

Abstract

We present TweetMotif, an exploratory search applica- tion for Twitter. Unlike traditional approaches to in- formation retrieval, which present a simple list of mes- sages, TweetMotif groups messages by frequent signif- icant terms — a result set’s subtopics — which facili- tate navigation and drilldown through a faceted search interface. The topic extraction system is based on syn- tactic filtering, language modeling, near-duplicate de- tection, and set cover heuristics. We have used Tweet- Motif to deflate rumors, uncover scams, summarize sentiment, and track political protests in real-time. A demo of TweetMotif, plus its source code, is available at http://tweetmotif.com.

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Published

2010-05-16

How to Cite

O’Connor, B., Krieger, M., & Ahn, D. (2010). TweetMotif: Exploratory Search and Topic Summarization for Twitter. Proceedings of the International AAAI Conference on Web and Social Media, 4(1), 384-385. https://doi.org/10.1609/icwsm.v4i1.14008