Affiliation:
1. Institute of Software Technology, Graz University of Technology, Graz, Austria
2. Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands
Abstract
Psychological factors such as
personality, emotions, social connections
, and
decision biases
can significantly affect the outcome of a decision process. These factors are also prevalent in the existing literature related to the inclusion of psychological aspects in recommender system development.
Personality
and
emotions
of users have strong connections with their interests and decision-making behavior. Hence, integrating these factors into recommender systems can help to better predict users’ item preferences and increase the satisfaction with recommended items. In scenarios where decisions are made by groups (e.g., selecting a tourism destination to visit with friends),
group composition
and
social connections
among group members can affect the outcome of a group decision.
Decision biases
often occur in a recommendation process, since users usually apply heuristics when making a decision. These biases can result in low-quality decisions. In this article, we provide a rigorous review of existing research on the influence of the mentioned psychological factors on recommender systems. These factors are not only considered in single-user recommendation scenarios but, importantly, also in group recommendation ones, where groups of users are involved in a decision-making process. We include working examples to provide a deeper understanding of how to take into account these factors in recommendation processes. The provided examples go beyond single-user recommendation scenarios by also considering specific aspects of group recommendation settings.
Funder
European Commission - H2020 ICT Program
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Human-Computer Interaction
Cited by
13 articles.
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