University of Oulu

Jahan, M. S., & Oussalah, M. (2023). A systematic review of hate speech automatic detection using natural language processing. Neurocomputing, 546, 126232.

A systematic review of hate speech automatic detection using natural language processing

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Author: Jahan, Md Saroar1; Oussalah, Mourad1
Organizations: 1University of Oulu, CMVS, BP 4500, 90014 Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 4.1 MB)
Persistent link:
Language: English
Published: Elsevier, 2023
Publish Date: 2023-09-22


With the multiplication of social media platforms, which offer anonymity, easy access and online community formation and online debate, the issue of hate speech detection and tracking becomes a growing challenge to society, individual, policy-makers and researchers. Despite efforts for leveraging automatic techniques for automatic detection and monitoring, their performances are still far from satisfactory, which constantly calls for future research on the issue. This paper provides a systematic review of literature in this field, with a focus on natural language processing and deep learning technologies, highlighting the terminology, processing pipeline, core methods employed, with a focal point on deep learning architecture. From a methodological perspective, we adopt PRISMA guideline of systematic review of the last 10 years literature from ACM Digital Library and Google Scholar. In the sequel, existing surveys, limitations, and future research directions are extensively discussed.

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Series: Neurocomputing
ISSN: 0925-2312
ISSN-E: 1872-8286
ISSN-L: 0925-2312
Volume: 546
Article number: 126232
DOI: 10.1016/j.neucom.2023.126232
Type of Publication: A2 Review article in a scientific journal
Field of Science: 213 Electronic, automation and communications engineering, electronics
Copyright information: © 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (