Beyond hostile linguistic cues: The gravity of online milieu for hate speech detection in Arabic

Arijit Ghosh Chowdhury, Aniket Didolkar, Ramit Sawhney, Rajiv Ratn Shah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Religious Hate speech poses grave dangers for the cohesion of a democratic society, the protection of human rights and the rule of law. While previous work has shown that linguistic features can be effectively used for text categorization in Arabic, employing information coming from users'social networks has not yet been explored for such complex user characteristics. Systems relying on language information tend to have low precision because they tend to rely on messages containing particular terms indicating hate speech. In this paper, we study the novel problem of exploiting social context for detection of religious hate speech in Arabic tweets, given information extracted from their online milieu by learning a low-dimensional vector representation of users.

Original languageEnglish
Title of host publicationHT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media
PublisherAssociation for Computing Machinery, Inc
Pages285-286
Number of pages2
ISBN (Electronic)9781450368858
DOIs
Publication statusPublished - 12-09-2019
Externally publishedYes
Event30th ACM Conference on Hypertext and Social Media, HT 2019 - Hof, Germany
Duration: 17-09-201920-09-2019

Publication series

NameHT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media

Conference

Conference30th ACM Conference on Hypertext and Social Media, HT 2019
CountryGermany
CityHof
Period17-09-1920-09-19

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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    Chowdhury, A. G., Didolkar, A., Sawhney, R., & Shah, R. R. (2019). Beyond hostile linguistic cues: The gravity of online milieu for hate speech detection in Arabic. In HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media (pp. 285-286). (HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media). Association for Computing Machinery, Inc. https://doi.org/10.1145/3342220.3344930