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Matching tweets with applicable fact-checks across languages

Abstract:

An important challenge for news fact-checking is the effective dissemination of existing fact-checks. This in turn brings the need for reliable methods to detect previously fact-checked claims. In this paper, we focus on automatically finding existing fact-checks for claims made in social media posts (tweets). We conduct both classification and retrieval experiments, in monolingual (English only), multilingual (Spanish, Portuguese), and cross-lingual (Hindi-English) settings using multilingua...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publication website:
https://ceur-ws.org/Vol-3199/

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Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Oxford college:
Hertford College
Role:
Author
ORCID:
0000-0002-6894-4951
Publisher:
CEUR Workshop Proceedings
Host title:
Proceedings of the Workshop on Multi-Modal Fake News and Hate-Speech Detection (DE-FACTIFY 2022) co-located with the Thirty-Sixth AAAI Conference on Artificial Intelligence ( AAAI 2022)
Series:
CEUR Workshop Proceedings
Series number:
3199
Publication date:
2022-08-25
Acceptance date:
2021-12-05
Event title:
De-Factify: Workshop on Multimodal Fact Checking and Hate Speech Detection, co-located with AAAI 2022
Event location:
Virtual Event, Vancouver, Canada
Event website:
https://aiisc.ai/defactify/
Event start date:
2022-02-28
Event end date:
2022-02-28
ISSN:
1613-0073
Language:
English
Keywords:
Pubs id:
1269786
Local pid:
pubs:1269786
Deposit date:
2023-05-11

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