The Role of Context in Detecting Previously Fact-Checked Claims

Anonymous

Paper Link: https://openreview.net/forum?id=_OLdnDdAgwm

Paper Type: Long paper (up to eight pages of content + unlimited references and appendices)

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.

Presentation Mode: This paper will be presented in person in Seattle

Copyright Consent Signature (type Name Or NA If Not Transferrable): Firoj Alam

Copyright Consent Name And Address: Firoj Alam, Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar