Group Recommender Systems aim to support the identification of items that best fit individual preferences of group members. However, decision making behavior of group members can be affected by decision biases which can deteriorate group decision quality. In this paper, we analyze the existence of Group Polarization Effects in two different domains and present a way to counteract these effects. Group Polarization is the tendency of a group to make decisions that are more extreme than the average of individual group members' preferences. We analyze Group Polarization in the context of risk analysis and cost estimation. In risk related group decisions, we figured out that if individual group members tend to make cautious decisions, then the group decision will be more cautious. However, in decisions related to cost estimation, the group estimations are lower than the average of group members' estimations (i.e., cautious shift). Furthermore, our results show that individual group members with diverse preferences are not influenced by Group Polarization Effects. The diversity in preferences of individual group members helps to counteract Group Polarization Effects.
|Titel||UMAP 2018: Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization|
|Publikationsstatus||Veröffentlicht - 2018|
|Veranstaltung||26th Conference on User Modeling, Adaptation and Personalization - Nanyang Technological University, Singapur|
Dauer: 8 Jul 2018 → 11 Jul 2018
|Konferenz||26th Conference on User Modeling, Adaptation and Personalization|
|Zeitraum||8/07/18 → 11/07/18|