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How many bits per rating?, , , , and . RecSys, page 99-106. ACM, (2012)User Personality and User Satisfaction with Recommender Systems., , , and . Inf. Syst. Frontiers, 20 (6): 1173-1189 (2018)Predicting Users' Preference from Tag Relevance., and . UMAP, volume 7899 of Lecture Notes in Computer Science, page 274-280. Springer, (2013)Improving recommender systems: user roles and lifecycles.. RecSys, page 417-420. ACM, (2014)Exploring the filter bubble, , , , and . Proceedings of the 23rd international conference on World wide web - WWW \textquotesingle14, ACM Press, (2014)Exploring the filter bubble: the effect of using recommender systems on content diversity., , , , and . WWW, page 677-686. ACM, (2014)Personality, User Preferences and Behavior in Recommender systems., , and . Inf. Syst. Frontiers, 20 (6): 1241-1265 (2018)Early Activity Diversity: Assessing Newcomer Retention from First-Session Activity., , and . CSCW, page 594-607. ACM, (2016)User Session Identification Based on Strong Regularities in Inter-activity Time., , , , , , , and . WWW, page 410-418. ACM, (2015)Exploring the Value of Personality in Predicting Rating Behaviors: A Study of Category Preferences on MovieLens., , and . RecSys, page 139-142. ACM, (2016)