Gaze-based Interest Detection on Newspaper Articles

Soumy Jacob, Shoya Ishimaru, Syed Saqib Bukhari, Andreas Dengel

In: Proceedings of the The 10th anniversary of the ACM Symposium on Eye Tracking Research & Applications (Hrsg.). ACM Symposium on Eye Tracking Research & Applications. Symposium on Eye Tracking Research & Applications (ETRA-2018) 7th International Workshop on Pervasive Eye Tracking and Mobile Eye-Based Interaction June 14-17 Warsaw Poland ACM 2018.


Eye tracking measures have been used to recognize cognitive states involving mental workload, comprehension, and self-confidence in the task of reading. In this paper, we present how these measures can be used to detect the interest of a reader. From the reading behavior of 13 university students on 18 newspaper articles, we have extracted features related to fixations, saccades, blinks and pupil diameters to detect which documents each participant finds interesting or uninteresting. We have classified their level of interests into four classes with an accuracy of 44% using eye movements, and it has increased to 62% if a survey about subjective comprehension is included. This research can be incorporated in the real-time prediction of a user's interest while reading, for the betterment of future designs of human-document interaction.

Weitere Links

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence