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Graph-Based Features for Automatic Online Abuse Detection

  • Etienne Papegnies
  • Vincent Labatut
  • Richard Dufour
  • Georges Linarès
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10583)

Abstract

While online communities have become increasingly important over the years, the moderation of user-generated content is still performed mostly manually. Automating this task is an important step in reducing the financial cost associated with moderation, but the majority of automated approaches strictly based on message content are highly vulnerable to intentional obfuscation. In this paper, we discuss methods for extracting conversational networks based on raw multi-participant chat logs, and we study the contribution of graph features to a classification system that aims to determine if a given message is abusive. The conversational graph-based system yields unexpectedly high performance, with results comparable to those previously obtained with a content-based approach.

Keywords

Text categorization Abuse detection Online communities Moderation 

Notes

Acknowledgments

This work was financed by a grant from the Provence Alpes Cte d’Azur region (France) and the Nectar de Code company.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Etienne Papegnies
    • 1
    • 2
  • Vincent Labatut
    • 1
  • Richard Dufour
    • 1
  • Georges Linarès
    • 1
  1. 1.LIA – EA 4128, University of AvignonAvignonFrance
  2. 2.Nectar de CodeBarbentaneFrance

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