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Social Event Detection on Twitter

  • Elena Ilina
  • Claudia Hauff
  • Ilknur Celik
  • Fabian Abel
  • Geert-Jan Houben
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7387)

Abstract

Various applications are developed today on top of microblogging services like Twitter. In order to engineer Web applications which operate on microblogging data, there is a need for appropriate filtering techniques to identify messages. In this paper, we focus on detecting Twitter messages (tweets) that report on social events. We introduce a filtering pipeline that exploits textual features and n-grams to classify messages into event related and non-event related tweets. We analyze the impact of preprocessing techniques, achieving accuracies higher than 80%. Further, we present a strategy to automate labeling of training data, since our proposed filtering pipeline requires training data. When testing on our dataset, this semi-automated method achieves an accuracy of 79% and results comparable to the manual labeling approach.

Keywords

microblogging Twitter event detection classification semi-automatic training 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Elena Ilina
    • 1
  • Claudia Hauff
    • 1
  • Ilknur Celik
    • 2
  • Fabian Abel
    • 1
  • Geert-Jan Houben
    • 1
  1. 1.Web Information SystemsDelft University of TechnologyThe Netherlands
  2. 2.Middle East Technical UniversityTurkey

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