TY - JOUR
T1 - Humanized Recommender Systems
T2 - State-of-the-art and Research Issues
AU - Tran, Thi Ngoc Trang
AU - Felfernig, Alexander
AU - Tintarev, Nava
PY - 2021/7
Y1 - 2021/7
N2 - 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.
AB - 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.
KW - decision biases
KW - group dynamics
KW - group recommender systems
KW - human decision making
KW - psychological factors
KW - Recommender systems
UR - http://www.scopus.com/inward/record.url?scp=85111465841&partnerID=8YFLogxK
U2 - 10.1145/3446906
DO - 10.1145/3446906
M3 - Article
AN - SCOPUS:85111465841
SN - 2160-6455
VL - 11
JO - ACM Transactions on Interactive Intelligent Systems
JF - ACM Transactions on Interactive Intelligent Systems
IS - 2
M1 - 9
ER -