Personality, User Preferences and Behavior in Recommender systems.
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| Title: | Personality, User Preferences and Behavior in Recommender systems. |
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| Authors: | Karumur, Raghav Pavan1 raghav@umn.edu, Nguyen, Tien T.1, Konstan, Joseph A.1 |
| Source: | Information Systems Frontiers. Dec2018, Vol. 20 Issue 6, p1241-1265. 25p. 1 Diagram, 12 Charts, 1 Graph. |
| Subjects: | Computer user attitudes, Personality assessment, Consumer behavior, Consumer preferences, Customer retention |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Information Systems Frontiers is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 13873326 |
| DOI: | 10.1007/s10796-017-9800-0 |
