RUHate-MM: Identification of Hate Speech and Targets using Multimodal Data from Russia-Ukraine Crisis-Reference-Cited by-同舟云学术

RUHate-MM: Identification of Hate Speech and Targets using Multimodal Data from Russia-Ukraine Crisis

Published:2024-05-13 Issue: Volume:33 Page:1854-1863
ISSN:
Container-title:Companion Proceedings of the ACM Web Conference 2024
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Author:

Thapa Surendrabikram¹^ORCID,Jafri Farhan Ahmad²^ORCID,Rauniyar Kritesh³^ORCID,Nasim Mehwish⁴^ORCID,Naseem Usman⁵^ORCID

Affiliation:

1. Virginia Tech, Blacksburg, VA, USA

2. Jamia Millia Islamia, New Delhi, India

3. Delhi Technological University, New Delhi, India

4. University of Western Australia & Flinders University, Perth, Western Australia, Australia

5. Macquarie University, Sydney, New South Wales, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589335.3651973

Reference38 articles.

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2. Firoj Alam, Stefano Cresci, Tanmoy Chakraborty, Fabrizio Silvestri, Dimiter Dimitrov, Giovanni Da San Martino, Shaden Shaar, Hamed Firooz, and Preslav Nakov. 2022. A Survey on Multimodal Disinformation Detection. In Proceedings of the 29th International Conference on Computational Linguistics. 6625--6643.

3. CrisisHateMM: Multimodal Analysis of Directed and Undirected Hate Speech in Text-Embedded Images from Russia-Ukraine Conflict

4. Sebastian Bock, Josef Goppold, and Martin Weiß. 2018. An improvement of the convergence proof of the ADAM-Optimizer. arXiv preprint arXiv:1804.10587 (2018).

5. Jean-Christophe Boucher. 2022. Disinformation and Russia-Ukrainian War on Canadian Social Media. The School of Public Policy Publications, Vol. 15, 1 (2022).

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