Connecting the Dots Between Fact Verification and Fake News Detection

Qifei Li, Wangchunshu Zhou

Abstract
Fact verification models have enjoyed a fast advancement in the last two years with the development of pre-trained language models like BERT and the release of large scale datasets such as FEVER. However, the challenging problem of fake news detection has not benefited from the improvement of fact verification models, which is closely related to fake news detection. In this paper, we propose a simple yet effective approach to connect the dots between fact verification and fake news detection. Our approach first employs a text summarization model pre-trained on news corpora to summarize the long news article into a short claim. Then we use a fact verification model pre-trained on the FEVER dataset to detect whether the input news article is real or fake. Our approach makes use of the recent success of fact verification models and enables zero-shot fake news detection, alleviating the need of large scale training data to train fake news detection models. Experimental results on FakenewsNet, a benchmark dataset for fake news detection, demonstrate the effectiveness of our proposed approach.
Anthology ID:
2020.coling-main.165
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
1820–1825
Language:
URL:
https://aclanthology.org/2020.coling-main.165
DOI:
10.18653/v1/2020.coling-main.165
Bibkey:
Cite (ACL):
Qifei Li and Wangchunshu Zhou. 2020. Connecting the Dots Between Fact Verification and Fake News Detection. In Proceedings of the 28th International Conference on Computational Linguistics, pages 1820–1825, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Connecting the Dots Between Fact Verification and Fake News Detection (Li & Zhou, COLING 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.coling-main.165.pdf
Data
FEVER, FakeNewsNet
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