Factuality Checking in News Headlines with Eye Tracking

Christian Hansen, Casper Hansen, Jakob Grue Simonsen, Birger Larsen, Stephen Alstrup, Christina Lioma

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1 Citationer (Scopus)

Abstrakt

We study whether it is possible to infer if a news headline is true or false using only the movement of the human eyes when reading news headlines. Our study with 55 participants who are eye-tracked when reading 108 news headlines (72 true, 36 false) shows that false headlines receive statistically significantly less visual attention than true headlines. We further build an ensemble learner that predicts news headline factuality using only eye-tracking measurements. Our model yields a mean AUC of 0.688 and is better at detecting false than true headlines. Through a model analysis, we find that eye-tracking 25 users when reading 3-6 headlines is sufficient for our ensemble learner.
OriginalsprogEngelsk
TitelProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Antal sider4
ForlagAssociation for Computing Machinery
Publikationsdato25 jul. 2020
Sider2013-2016
ISBN (Elektronisk)9781450380164
DOI
StatusUdgivet - 25 jul. 2020
Begivenhed43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 - Virtual, Online, Kina
Varighed: 25 jul. 202030 jul. 2020

Konference

Konference43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020
Land/OmrådeKina
ByVirtual, Online
Periode25/07/202030/07/2020
SponsorSpecial Interest Group on Information Retrieval (ACM SIGIR)

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