Abstract
Diversifying recommendations has shown to be a good means
to counteract on choice difficulties and overload, and is able to positively influence subjective evaluations, such as satisfaction and attractiveness.
Personal characteristics (e.g., domain expertise, prior preference strength) have shown to influence the desired level of diversity in a recommendation
list. However, only personal characteristics that are directly related to the domain have been investigated so far. In this
work we take personality traits as a general user model and show that specific traits are related to a preference for different levels of diversity
(in terms of recommendation satisfaction and attractiveness). Among 103 participants we show that conscientiousness is related to a preference for a
higher degree of diversification, while agreeableness is related to a mid-level diversification of the recommendations. Our results have implications
on how to personalize recommendation lists (i.e., the amount of diversity that should be provided) depending on users' personality.
| Original language | English |
|---|---|
| Title of host publication | Extended Proceedings of the 10th ACM Recommender Systems (RecSys) Conference: 4th Workshop on Emotions and Personality in Personalized Systems (EMPIRE). |
| Number of pages | 5 |
| Publication status | Published - 2016 |
Fields of science
- 202002 Audiovisual media
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
JKU Focus areas
- Computation in Informatics and Mathematics
- Engineering and Natural Sciences (in general)