Our paper “A System to Monitor Cyberbullying based on Message Classification and Social Network Analysis” authored by Stefano Menini, Giovanni Moretti, Michele Corazza, Elena Cabrio, Sara Tonelli and Serena Villata has been accepted at the 3th Abusive Language Workshop, that will take place 1 August in Florence, co-located with ACL2019.


Social media platforms like Twitter and Instagram face the issue of detecting cyberbullying phenomena against young users, in order to limit the negative (and sometimes fatal) consequences of this kind of abuse. Despite the number of approaches recently proposed in the Natural Language Processing research area for detecting different forms of abusive language, the issue of identifying cyberbullying phenomena at scale is still an unsolved problem. This is because of the need to couple abusive language detection on textual message with network analysis, so that repeated attacks against the same person can be identified. In this paper, we present a system to monitor cyberbullying phenomena by combining message classification and social network analysis. We evaluate the classification module on a data set built on Instagram messages, and we describe the cyberbullying monitoring user interface.

The system has been developed in the framework of the Cyberbullying Effects Prevention (CREEP) Project, funded by EIT Digital, and the HATEMETER project.