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Extracting Social Events Based on Timeline and Sentiment Analysis in Twitter Corpus

  • Bayar Tsolmon
  • A-Rong Kwon
  • Kyung-Soon Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7337)

Abstract

We propose a novel method for extracting social events based on timeline and sentiment analysis from social streams such as Twitter. When a big social issue or event occurs, it tends to dramatically increase in the number of tweets. Users write tweets to express their opinions. Our method uses these timeline and sentiment properties of social media streams to extract social events. On timelines term significance is calculated based on Chi-square measure. Evaluating the method on Korean tweet collection for 30 events, our method achieved 94.3% in average precision in the top 10 extracted events. The result indicates that our method is effective for social event extraction.

Keywords

Event extraction Timeline Sentiment Chi-Square Twitter 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bayar Tsolmon
    • 1
  • A-Rong Kwon
    • 1
  • Kyung-Soon Lee
    • 1
  1. 1.Division of Computer Science and EngineeringChonbuk National UniversityJeonju-siRepublic of Korea

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