Group Modeling, Adaptation and Personalization

Group modeling adaptation and personalization is an area explored in parallel by two different research communities. On the one side, the user modeling community focuses on the preferences aggregation problem: how to combine preferences of individuals in a group so as to personalize, adapt, and explain content for this group to consume or experience? On the other side, the computer-supported collaboration community focuses on the group formation problem: how to construct a group that will work together efficiently to solve a particular task? This area becomes increasingly significant as work becomes more flexible, online, and distributed. The connecting tissue between both communities is the urgent need to design algorithms, whether for recommending group content or group formations, that steer away from top-down algorithmic decision-making, which has proven to stifle user agency and create power inequalities between users and algorithms. The aim of the workshop is, for the first time, to bring together the two communities working on the two sides of Group Recommendations, inviting academics and researchers to share their contributions, work-in-progress and latest research results with an overall goal to rethink group recommendation and shift paradigms from the current algorithm-centric to user- and group-centric focus.