Exploring automatic hate speech detection on social media: a focus on content-based analysis

NASCIMENTO, Francimaria R. S., CAVALCANTI, George D. C. and DA COSTA-ABREU, Márjory (2023). Exploring automatic hate speech detection on social media: a focus on content-based analysis. SAGE Open, 13 (2).

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Abstract

Hate speech is a challenging problem, and its dissemination can cause potential harm to individuals and society by creating a sense of general unwelcoming to the marginalized groups, which usually are targeted. Therefore, it is essential to understand this issue and which techniques are useful for automatic detection. This paper presents a survey on automatic hate speech detection on social media, providing a structured overview of theoretical aspects and practical resources. Thus, we review different definitions of the term “hate speech” from social network platforms and the scientific community. We also present an overview of the methodologies used for hate speech detection, and we describe the main approaches currently explored in this context, including popular features, datasets, and algorithms. Furthermore, we discuss some challenges and opportunities for better solving this issue.

Item Type:	Article
Additional Information:	** Embargo end date: 17-06-2023 ** From SAGE Publishing via Jisc Publications Router ** Licence for this article starting on 17-06-2023: https://creativecommons.org/licenses/by/4.0/ ** Peer reviewed: TRUE **Journal IDs: eissn 2158-2440 **Article IDs: publisher-id: 10.1177_21582440231181311 **History: published_online 17-06-2023
Uncontrolled Keywords:	natural language processing, metadata, survey, social media, hate speech detection, text features
Identification Number:	https://doi.org/10.1177/21582440231181311
SWORD Depositor:	Colin Knott
Depositing User:	Colin Knott
Date Deposited:	19 Jun 2023 14:38
Last Modified:	20 Jun 2023 15:29
URI:	https://shura.shu.ac.uk/id/eprint/32029

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