Personality, User Preferences and Behavior in Recommender systems

This paper reports on a study of 1840 users of the MovieLens recommender system with identified Big-5 personality types. Based on prior literature that suggests that personality type is a stable predictor of user preferences and behavior, we examine factors of user retention and engagement, content...

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Bibliographic Details
Published inInformation systems frontiers Vol. 20; no. 6; pp. 1241 - 1265
Main Authors Karumur, Raghav Pavan, Nguyen, Tien T., Konstan, Joseph A.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.12.2018
Springer Nature B.V
Subjects
Behavior
Business and Management
Control
Information systems
IT in Business
Management of Computing and Information Systems
Operations Research/Decision Theory
Personality
Recommender systems
Systems Theory
Personality
User preferences
Newcomer retention
Recommender systems
Big-five personality traits
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Summary:This paper reports on a study of 1840 users of the MovieLens recommender system with identified Big-5 personality types. Based on prior literature that suggests that personality type is a stable predictor of user preferences and behavior, we examine factors of user retention and engagement, content preferences, and rating patterns to identify recommender-system related behaviors and preferences that correlate with user personality. We find that personality traits correlate significantly with behaviors and preferences such as newcomer retention, intensity of engagement, activity types, item categories, consumption versus contribution, and rating patterns.
ISSN:1387-3326
1572-9419
DOI:10.1007/s10796-017-9800-0