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ClaimBuster: A Benchmark Dataset of Check-worthy Factual Claims

Authors: Fatma Arslan; Naeemul Hassan; Chengkai Li; Mark Tremayne;

ClaimBuster: A Benchmark Dataset of Check-worthy Factual Claims

Abstract

The ClaimBuster dataset consists of statements extracted from all U.S. general election presidential debates (1960-2016) along with human-annotated check-worthiness labels where each sentence is categorized into one of the three categories: non-factual statement, unimportant factual statement, and check-worthy factual statement. If you use this dataset, please cite the following paper: @inproceedings{arslan2020claimbuster, title={{A Benchmark Dataset of Check-worthy Factual Claims}}, author={Arslan, Fatma and Hassan, Naeemul and Li, Chengkai and Tremayne, Mark }, booktitle={14th International AAAI Conference on Web and Social Media}, year={2020}, organization={AAAI} }

The work is partially supported by NSF grants IIS-1408928, IIP-1565699, IIS-1719054, OIA-1937143, a Knight Prototype Fund from the Knight Foundation, and subawards from Duke University as part of a grant to the Duke Tech & Check Cooperative from the Knight Foundation and Facebook. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the funding agencies.

Keywords

factual claim, check-worthiness, check-worthy claim

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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