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2014 | OriginalPaper | Buchkapitel

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

verfasst von : Maral Dadvar, Dolf Trieschnigg, Franciska de Jong

Erschienen in: Advances in Artificial Intelligence

Verlag: Springer International Publishing

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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.

Metadaten
Titel
Experts and Machines against Bullies: A Hybrid Approach to Detect Cyberbullies
verfasst von
Maral Dadvar
Dolf Trieschnigg
Franciska de Jong
Copyright-Jahr
2014
Verlag
Springer International Publishing
DOI
https://doi.org/10.1007/978-3-319-06483-3_25

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