Humanized Recommender Systems: State-of-the-art and Research Issues

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article number9
Number of pages41
JournalACM Transactions on Interactive Intelligent Systems
Issue number2
Publication statusPublished - Jul 2021


  • decision biases
  • group dynamics
  • group recommender systems
  • human decision making
  • psychological factors
  • Recommender systems

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Artificial Intelligence


Dive into the research topics of 'Humanized Recommender Systems: State-of-the-art and Research Issues'. Together they form a unique fingerprint.

Cite this