User Interfaces for Counteracting Decision Manipulation in Group Recommender Systems

Research output: Contribution to conferencePosterResearchpeer-review

Abstract

In group recommender systems,decision manipulation refers to an attack in which a group member makes attempts to push his/her favorite options. In this paper, we propose user interfaces to counteract decision manipulation in group recommender systems. The proposed user interfaces visualize information dimensions regarding rating adaptations of group members at different transparency levels. The results show that the user interface at the highest transparency level best helps to discourage users from decision manipulation. Besides, the ability of the user interfaces to counteract decision manipulation differs depending on the dimensions represented in the user interfaces. The information dimensions regarding item ratings and group recommendations have the strongest impacts on preventing users from decision manipulation.
Original languageEnglish
Publication statusPublished - Jun 2019
Event27th ACM Conference on User Modeling, Adaptation and Personalization - Larnaca, Cyprus
Duration: 9 Jun 201912 Jun 2019

Conference

Conference27th ACM Conference on User Modeling, Adaptation and Personalization
Abbreviated titleUMAP 2019
CountryCyprus
CityLarnaca
Period9/06/1912/06/19

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Keywords

  • group decision making
  • group recommender systems
  • user interfaces
  • decision biases
  • decision manipulation

Cite this

Tran, T. N. T., Felfernig, A., Le, V. M., Atas, M., Stettinger, M., & Samer, R. (2019). User Interfaces for Counteracting Decision Manipulation in Group Recommender Systems. Poster session presented at 27th ACM Conference on User Modeling, Adaptation and Personalization, Larnaca, Cyprus.