BullStop: A Mobile App for Cyberbullying Prevention

Abstract

Social media has become the new playground for bullies. Young people are now regularly exposed to a wide range of abuse online. In response to the increasing prevalence of cyberbullying, online social networks have increased efforts to clamp down on online abuse but unfortunately, the nature, complexity and sheer volume of cyberbullying means that many cyberbullying incidents go undetected. BullStop is a mobile app for detecting and preventing cyberbullying and online abuse on social media platforms. It uses deep learning models to identify instances of cyberbullying and can automatically initiate actions such as deleting offensive messages and blocking bullies on behalf of the user. Our system not only achieves impressive prediction results but also demonstrates excellent potential for use in real-world scenarios and is freely available on the Google Play Store.

Publication DOI: https://doi.org/10.18653/v1/2020.coling-demos.13
Divisions: College of Engineering & Physical Sciences > Aston STEM Education Centre
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College of Engineering & Physical Sciences > Aston Institute of Urban Technology and the Environment (ASTUTE)
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences
Additional Information: This work is licensed under a Creative Commons Attribution 4.0 International Licence. Licence details: https://creativecommons.org/licenses/by/4.0/
Event Title: The 28th International Conference on Computational Linguistics
Event Type: Other
Event Dates: 2020-12-08 - 2020-12-13
ISBN: 9781952148286
Last Modified: 27 Mar 2024 18:50
Date Deposited: 01 Apr 2022 14:11
Full Text Link:
Related URLs: https://aclanth ... oling-demos.13/ (Publisher URL)
PURE Output Type: Chapter (peer-reviewed)
Published Date: 2020-12
Authors: Salawu, Semiu
He, Yulan (ORCID Profile 0000-0003-3948-5845)
Lumsden, Jo (ORCID Profile 0000-0002-8637-7647)

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