@inproceedings{menini-etal-2019-system,
title = "A System to Monitor Cyberbullying based on Message Classification and Social Network Analysis",
author = "Menini, Stefano and
Moretti, Giovanni and
Corazza, Michele and
Cabrio, Elena and
Tonelli, Sara and
Villata, Serena",
editor = "Roberts, Sarah T. and
Tetreault, Joel and
Prabhakaran, Vinodkumar and
Waseem, Zeerak",
booktitle = "Proceedings of the Third Workshop on Abusive Language Online",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-3511",
doi = "10.18653/v1/W19-3511",
pages = "105--110",
abstract = "Social media platforms like Twitter and Instagram face a surge in cyberbullying phenomena against young users and need to develop scalable computational methods to limit the negative consequences of this kind of abuse. Despite the number of approaches recently proposed in the Natural Language Processing (NLP) 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.",
}
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<abstract>Social media platforms like Twitter and Instagram face a surge in cyberbullying phenomena against young users and need to develop scalable computational methods to limit the negative consequences of this kind of abuse. Despite the number of approaches recently proposed in the Natural Language Processing (NLP) 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.</abstract>
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%0 Conference Proceedings
%T A System to Monitor Cyberbullying based on Message Classification and Social Network Analysis
%A Menini, Stefano
%A Moretti, Giovanni
%A Corazza, Michele
%A Cabrio, Elena
%A Tonelli, Sara
%A Villata, Serena
%Y Roberts, Sarah T.
%Y Tetreault, Joel
%Y Prabhakaran, Vinodkumar
%Y Waseem, Zeerak
%S Proceedings of the Third Workshop on Abusive Language Online
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F menini-etal-2019-system
%X Social media platforms like Twitter and Instagram face a surge in cyberbullying phenomena against young users and need to develop scalable computational methods to limit the negative consequences of this kind of abuse. Despite the number of approaches recently proposed in the Natural Language Processing (NLP) 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.
%R 10.18653/v1/W19-3511
%U https://aclanthology.org/W19-3511
%U https://doi.org/10.18653/v1/W19-3511
%P 105-110
Markdown (Informal)
[A System to Monitor Cyberbullying based on Message Classification and Social Network Analysis](https://aclanthology.org/W19-3511) (Menini et al., ALW 2019)
ACL