ExU: AI Models for Examining Multilingual Disinformation Narratives and Understanding their Spread

Jake Vasilakes, Zhixue Zhao, Michal Gregor, Ivan Vykopal, Martin Hyben, Carolina Scarton


Abstract
Addressing online disinformation requires analysing narratives across languages to help fact-checkers and journalists sift through large amounts of data. The ExU project focuses on developing AI-based models for multilingual disinformation analysis, addressing the tasks of rumour stance classification and claim retrieval. We describe the ExU project proposal and summarise the results of a user requirements survey regarding the design of tools to support fact-checking.
Anthology ID:
2024.eamt-2.20
Volume:
Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 2)
Month:
June
Year:
2024
Address:
Sheffield, UK
Editors:
Carolina Scarton, Charlotte Prescott, Chris Bayliss, Chris Oakley, Joanna Wright, Stuart Wrigley, Xingyi Song, Edward Gow-Smith, Mikel Forcada, Helena Moniz
Venue:
EAMT
SIG:
Publisher:
European Association for Machine Translation (EAMT)
Note:
Pages:
39–40
Language:
URL:
https://aclanthology.org/2024.eamt-2.20
DOI:
Bibkey:
Cite (ACL):
Jake Vasilakes, Zhixue Zhao, Michal Gregor, Ivan Vykopal, Martin Hyben, and Carolina Scarton. 2024. ExU: AI Models for Examining Multilingual Disinformation Narratives and Understanding their Spread. In Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 2), pages 39–40, Sheffield, UK. European Association for Machine Translation (EAMT).
Cite (Informal):
ExU: AI Models for Examining Multilingual Disinformation Narratives and Understanding their Spread (Vasilakes et al., EAMT 2024)
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PDF:
https://preview.aclanthology.org/add_acl24_videos/2024.eamt-2.20.pdf