You Do Not Decide for Me!

You Do Not Decide for Me!: Evaluating Explainable Group Aggregation Strategies for Tourism

Najafian, S. (TU Delft Web Information Systems)
Herzog, Daniel (Technische Universität München)
Qiu, S. (TU Delft Web Information Systems)
Inel, O. (TU Delft Web Information Systems)
Tintarev, N. (TU Delft Web Information Systems)

2020

Most recommender systems propose items to individual users. However, in domains such as tourism, people often consume items in groups rather than individually. Different individual preferences in such a group can be difficult to resolve, and often compromises need to be made. Social choice strategies can be used to aggregate the preferences of individuals. We evaluated two explainable modified preference aggregation strategies in a between-subject study (n=200), and compared them with two baseline strategies for groups that are also explainable, in two scenarios: high divergence (group members with different travel preferences) and low divergence (group members with similar travel preferences). Generally, all investigated aggregation strategies performed well in terms of perceived individual and group satisfaction and perceived fairness. The results also indicate that participants were sensitive to a dictator-based strategy, which affected both their individual and group satisfaction negatively (compared to the other strategies).

Explainable aggregation strategies
Group recommendation
Human-centered computing user studies

http://resolver.tudelft.nl/uuid:6cf52d4a-8ea2-48a8-8c55-c776c92ac62b

https://doi.org/10.1145/3372923.3404800

978-1-4503-7098-1

Proceedings of the 31st ACM Conference on Hypertext and Social Media (HT ’20),

HT'20: 31st ACM Conference on Hypertext and Social Media, 2020-07-13 → 2020-07-15, Online event, United States

Institutional Repository

conference paper

© 2020 S. Najafian, Daniel Herzog, S. Qiu, O. Inel, N. Tintarev