Factuality Checking in News Headlines with Eye Tracking

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

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Number of pages4
PublisherAssociation for Computing Machinery
Publication date25 Jul 2020
Pages2013-2016
ISBN (Electronic)9781450380164
DOIs
Publication statusPublished - 25 Jul 2020
Event43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 - Virtual, Online, China
Duration: 25 Jul 202030 Jul 2020

Conference

Conference43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020
Country/TerritoryChina
CityVirtual, Online
Period25/07/202030/07/2020
SponsorSpecial Interest Group on Information Retrieval (ACM SIGIR)

Keywords

  • eye tracking
  • factuality checking
  • fake news

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