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title
SecLab - Mean Birds: Detecting Aggression and Bullying on Twitter
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Mean Birds: Detecting Aggression and Bullying on Twitter  DownloadAuthorsDespoina Chatzakou, Nicolas Kourtellis, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, Athena VakaliVenueProceedings of the 2017 International ACM Web Science Conference (WebSci), June 2017AbstractIn recent years, bullying and aggression against social media users have grown signi cantly, causing serious consequences to victims of all demographics. Nowadays, cyberbullying a ects more than half of young social media users worldwide, su ering from prolonged and/or coordinated digital harassment. Also, tools and technologies geared to understand and mitigate it are scarce and mostly ine ective. In this paper, we present a principled and scalable approach to detect bullying and aggressive behavior on Twitter. We propose a robust methodology for extracting text, user, and network-based attributes, studying the properties of bullies and aggressors, and what features distinguish them from regular users. W...
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