Experts and Machines against Bullies: A Hybrid Approach to Detect Cyberbullies

  • Maral Dadvar
  • Dolf Trieschnigg
  • Franciska de Jong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8436)

Abstract

Cyberbullying is becoming a major concern in online environments with troubling consequences. However, most of the technical studies have focused on the detection of cyberbullying through identifying harassing comments rather than preventing the incidents by detecting the bullies. In this work we study the automatic detection of bully users on YouTube. We compare three types of automatic detection: an expert system, supervised machine learning models, and a hybrid type combining the two. All these systems assign a score indicating the level of “bulliness” of online bullies. We demonstrate that the expert system outperforms the machine learning models. The hybrid classifier shows an even better performance.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Maral Dadvar
    • 1
  • Dolf Trieschnigg
    • 1
  • Franciska de Jong
    • 1
  1. 1.Human Media Interaction GroupUniversity of TwenteEnschedeThe Netherlands

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