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 language | English |
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| Title of host publication | SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Number of pages | 4 |
| Publisher | Association for Computing Machinery |
| Publication date | 2020 |
| Pages | 2013-2016 |
| ISBN (Electronic) | 9781450380164 |
| DOIs | |
| Publication status | Published - 2020 |
| Event | 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 - Virtual, Online, China Duration: 25 Jul 2020 → 30 Jul 2020 |
Conference
| Conference | 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 |
|---|---|
| Country/Territory | China |
| City | Virtual, Online |
| Period | 25/07/2020 → 30/07/2020 |
| Sponsor | ACM Special Interest Group on Information Retrieval (SIGIR) |
Keywords
- eye tracking
- factuality checking
- fake news