Bruce Ferwerda, Mark Graus, Andreu Vall, Marko Tkalcic, Markus Schedl,
"The Influence of Users' Personality Traits on Satisfaction and Attractiveness of Diversified Recommendation Lists."
: Extended Proceedings of the 10th ACM Recommender Systems (RecSys) Conference: 4th Workshop on Emotions and Personality in Personalized Systems (EMPIRE)., 2016
Original Titel:
The Influence of Users' Personality Traits on Satisfaction and Attractiveness of Diversified Recommendation Lists.
Sprache des Titels:
Englisch
Original Buchtitel:
Extended Proceedings of the 10th ACM Recommender Systems (RecSys) Conference: 4th Workshop on Emotions and Personality in Personalized Systems (EMPIRE).
Original Kurzfassung:
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.