The Role of Context in Detecting Previously Fact-Checked Claims
Shaden Shaar, Firoj Alam, Giovanni Da San Martino, Preslav Nakov
Abstract
Recent years have seen the proliferation of disinformation and fake news online. Traditional approaches to mitigate these issues is to use manual or automatic fact-checking. Recently, another approach has emerged: checking whether the input claim has previously been fact-checked, which can be done automatically, and thus fast, while also offering credibility and explainability, thanks to the human fact-checking and explanations in the associated fact-checking article. Here, we focus on claims made in a political debate and we study the impact of modeling the context of the claim: both on the source side, i.e., in the debate, as well as on the target side, i.e., in the fact-checking explanation document. We do this by modeling the local context, the global context, as well as by means of co-reference resolution, and multi-hop reasoning over the sentences of the document describing the fact-checked claim. The experimental results show that each of these represents a valuable information source, but that modeling the source-side context is most important, and can yield 10+ points of absolute improvement over a state-of-the-art model.- Anthology ID:
- 2022.findings-naacl.122
- Volume:
- Findings of the Association for Computational Linguistics: NAACL 2022
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Editors:
- Marine Carpuat, Marie-Catherine de Marneffe, Ivan Vladimir Meza Ruiz
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1619–1631
- Language:
- URL:
- https://aclanthology.org/2022.findings-naacl.122
- DOI:
- 10.18653/v1/2022.findings-naacl.122
- Cite (ACL):
- Shaden Shaar, Firoj Alam, Giovanni Da San Martino, and Preslav Nakov. 2022. The Role of Context in Detecting Previously Fact-Checked Claims. In Findings of the Association for Computational Linguistics: NAACL 2022, pages 1619–1631, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- The Role of Context in Detecting Previously Fact-Checked Claims (Shaar et al., Findings 2022)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2022.findings-naacl.122.pdf
- Code
- firojalam/detecting-previously-fact-checked-claims
- Data
- FEVER, PolitiFact, Snopes