Abusive Language on Social Media Through the Legal Looking Glass

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review


Abusive language is a growing phenomenon on social media platforms. Its effects can reach beyond the online context, contributing to mental or emotional stress on users. Automatic tools for detecting abuse can alleviate the issue. In practice, developing automated methods to detect abusive language relies on good quality data. However, there is currently a lack of standards for creating datasets in the field. These standards include definitions of what is considered abusive language, annotation guidelines and reporting on the process. This paper introduces an annotation framework inspired by legal concepts to define abusive language in the context of online harassment. The framework uses a 7-point Likert scale for labelling instead of class labels. We also present ALYT – a dataset of Abusive Language on YouTube. ALYT includes YouTube comments in English extracted from videos on different controversial topics and labelled by Law students. The comments were sampled from the actual collected data, without artificial methods for increasing the abusive content. The paper describes the annotation process thoroughly, including all its guidelines and training steps.
Original languageEnglish
Title of host publicationWOAH 2021: THE 5TH WORKSHOP ON ONLINE ABUSE AND HARMS
PublisherAssociation for Computational Linguistics
Number of pages10
ISBN (Print)9781954085596
Publication statusPublished - Jun 2021
Event5th Workshop on Online Abuse and Harms (WOAH) - Virtual
Duration: 5 Aug 20216 Aug 2021


Conference5th Workshop on Online Abuse and Harms (WOAH)
Abbreviated titleWOAH 5
Internet address

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