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A Survey on Automatic Detection of Hate Speech in Text

Published:31 July 2018Publication History
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Abstract

The scientific study of hate speech, from a computer science point of view, is recent. This survey organizes and describes the current state of the field, providing a structured overview of previous approaches, including core algorithms, methods, and main features used. This work also discusses the complexity of the concept of hate speech, defined in many platforms and contexts, and provides a unifying definition. This area has an unquestionable potential for societal impact, particularly in online communities and digital media platforms. The development and systematization of shared resources, such as guidelines, annotated datasets in multiple languages, and algorithms, is a crucial step in advancing the automatic detection of hate speech.

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        • Published in

          cover image ACM Computing Surveys
          ACM Computing Surveys  Volume 51, Issue 4
          July 2019
          765 pages
          ISSN:0360-0300
          EISSN:1557-7341
          DOI:10.1145/3236632
          • Editor:
          • Sartaj Sahni
          Issue’s Table of Contents

          Copyright © 2018 ACM

          © 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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          Publication History

          • Published: 31 July 2018
          • Accepted: 1 June 2018
          • Revised: 1 May 2018
          • Received: 1 October 2017
          Published in csur Volume 51, Issue 4

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