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Using fuzzy fingerprints for cyberbullying detection in social networks

IEEE International Conference on Fuzzy Systems, ISSN: 1098-7584, Vol: 2018-July, Page: 1-7
2018
  • 36
    Citations
  • 0
    Usage
  • 41
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    36
    • Citation Indexes
      36
  • Captures
    41

Conference Paper Description

As cyberbullying becomes more and more frequent in social networks, automatically detecting it and pro-actively acting upon it becomes of the utmost importance. In this work, we study how a recent technique with proven success in similar tasks, Fuzzy Fingerprints, performs when detecting textual cyberbullying in social networks. Despite being commonly treated as binary classification task, we argue that this is in fact a retrieval problem where the only relevant performance is that of retrieving cyberbullying interactions. Experiments show that the Fuzzy Fingerprints slightly outperforms baseline classifiers when tested in a close to real life scenario, where cyberbullying instances are rarer than those without cyberbullying.

Bibliographic Details

Hugo Rosa; Pável Calado; Joao P. Carvalho; Bruno Martins; Luisa Coheur; Ricardo Ribeiro

Institute of Electrical and Electronics Engineers (IEEE)

Computer Science; Mathematics

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