Exploring Design Considerations for Group Recommendation Systems as a Social Catalyst

Group recommendation systems (GRS) provide personalized recommendations to multiple users. While GRS has garnered attention as a social catalyst that can foster social interactions among users, how to design GRS to effectively support such experiences remains underexplored. To address this gap, we conducted an empirical study of a YouTube video GRS involving 23 participants across 8 groups over 16 days. Using experience prototyping combined with a diary study and follow-up interviews, we investigated users’ perceptions of three design attributes of GRS: algorithmic controllability, algorithmic transparency, and behavioral visibility. Our findings reveal the social experiences enabled by these design attributes, as well as the challenges and concerns that emerged. Based on these findings, we conceptualize five roles of GRS as a social catalyst (i.e., Hinter, Connector, Probe, Homing Pigeon, and Provocateur ) and suggest design considerations for leveraging GRS as a novel design material to facilitate meaningful social interactions.