Your Turn To Roll: Exploring gaps in group recommendation research

In group recommendation, a key question is how preferences from individuals should be obtained and then aggregated into a group outcome. Collecting individual preferences can be done through implicit or explicit means, but there is insufficient research available on what option is optimal. For comparing different possible aggregation strategies, much of the existing research in the field departs from existing preference data (e.g.\ ratings), but considers synthetically created groups, rather than real groups. This study describes two experiments focusing on these issues. The first compared historical listening data with explicitly provided data and showed them to be similar. The second experiment compares different aggregation strategies in a more ecologically valid setting. More specifically, it considers playlist creation scenarios for groups, in which participants were asked to create their own, real-life groups. While the playlists as a whole did not show any significant differences in performance, inspecting the ratings of the tracks did show some differences. Finally, acoustic similarity was explored using the data obtained in the experiments. Some early results were observed, but more research is needed in this area.https://github.com/Austaon/GroupRecommendationThesis Link to the code used for the experiments and the datasets collected during the experiment