Adapting Recommendation Diversity to Openness to Experience: A Study of Human Behaviour

Nava Tintarev, Matthew Gordon Dennis, Judith Masthoff

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

38 Citations (Scopus)
11 Downloads (Pure)


This paper uses a User-as-Wizard approach to evaluate how people apply diversity to a set of recommendations. In particular, it considers how diversity is applied for a recipient with high or low Openness to Experience, a personality trait from the Five Factor Model. While there was no effect of the personality trait on the degree of diversity applied, there seems to be a trend in the way in which it was applied. Maximal categorical diversity (across genres) was more likely to be applied to those with high Openness to Experience, at the expense of maximal thematic diversity (within genres).
Original languageEnglish
Title of host publicationUser Modeling, Adaptation, and Personalization
Subtitle of host publication21th International Conference, UMAP 2013, Rome, Italy, June 10-14, 2013 Proceedings
EditorsSandra Carberry, Stephan Weibelzahl, Alessandro Micarelli, Giovanni Semeraro
Number of pages13
ISBN (Electronic)978-3-642-38844-6
ISBN (Print)978-3-642-38843-9
Publication statusPublished - 2013
Event21st International Conference on User Modeling, Adaptation and Personalization - Rome, Italy
Duration: 10 Jun 201314 Jun 2013

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


Conference21st International Conference on User Modeling, Adaptation and Personalization


  • diversity
  • serendipity
  • personality
  • recommender systems

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