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Original article (peer-reviewed)

Journal ACM Transactions on Intelligent Systems and Technology
Volume (Issue) To appear in 2014
Title of proceedings ACM Transactions on Intelligent Systems and Technology

Abstract

We designed and ran a between-groups experiment for measuring and eye-tracking social influence using a group music recommender system. In this paper, we analyze the extent to which people change their opinions when facing various individual preferences coming from their peers. In our study, we first asked participants to give ratings to group songs and then perform an eye-tracking task in which they saw others’ names and ratings and were asked to make a rating decision again. Our results focus on measuring group conformity through eye tracking, or the extent to which a person changed his/her own rating by means of creating eye gaze correspondences between others' names and ratings. Furthermore, the stronger social relationships through familiarity and trust are, the more individuals adopt the group decision and are more inclined to change their preferences. Also, the correspondences users make between peers’ names and their ratings represent a good indicator for understanding self-evaluation of a given song. Eye tracking outputs present clear associations between various areas of the interests while fixation times are useful to understand social influence relative to closest members in the group.
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