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 language | English |
|---|---|
| Title of host publication | HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 285-286 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781450368858 |
| DOIs | |
| Publication status | Published - 12-09-2019 |
| Externally published | Yes |
| Event | 30th ACM Conference on Hypertext and Social Media, HT 2019 - Hof, Germany Duration: 17-09-2019 → 20-09-2019 |
Publication series
| Name | HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media |
|---|
Conference
| Conference | 30th ACM Conference on Hypertext and Social Media, HT 2019 |
|---|---|
| Country | Germany |
| City | Hof |
| Period | 17-09-19 → 20-09-19 |
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All Science Journal Classification (ASJC) codes
- Software
- Artificial Intelligence
- Human-Computer Interaction
- Computer Graphics and Computer-Aided Design
Cite this
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Beyond hostile linguistic cues : The gravity of online milieu for hate speech detection in Arabic. / Chowdhury, Arijit Ghosh; Didolkar, Aniket; Sawhney, Ramit; Shah, Rajiv Ratn.
HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media. Association for Computing Machinery, Inc, 2019. p. 285-286 (HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Beyond hostile linguistic cues
T2 - The gravity of online milieu for hate speech detection in Arabic
AU - Chowdhury, Arijit Ghosh
AU - Didolkar, Aniket
AU - Sawhney, Ramit
AU - Shah, Rajiv Ratn
PY - 2019/9/12
Y1 - 2019/9/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85073359488&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073359488&partnerID=8YFLogxK
U2 - 10.1145/3342220.3344930
DO - 10.1145/3342220.3344930
M3 - Conference contribution
AN - SCOPUS:85073359488
T3 - HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media
SP - 285
EP - 286
BT - HT 2019 - Proceedings of the 30th ACM Conference on Hypertext and Social Media
PB - Association for Computing Machinery, Inc
ER -