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The motivation of this work comes from various psychological studies that demonstrate that psychological attributes such as personality and values can influence one\u2019s decision or choice in real life. In this work, we integrate user interactions in Twitter and IMDb to derive interesting relations between human psychological attributes and their movie preferences. In particular, we first predict a user\u2019s movie genre preferences from the personality and value scores of the user derived from her tweets. Second, we also develop models to predict user movie rating behavior from her tweets in Twitter and movie genre and storyline preferences from IMDb. We further strengthen the movie rating model by incorporating the user reviews. In the above models, we investigate the role of personality and values independently and combinedly while predicting movie genre preferences and movie rating behaviors. We find that our combined models significantly improve the accuracy than that of a single model that is built by using personality or values independently. We also compare our technique with the traditional movie genre and rating prediction techniques. The experimental results show that our models are effective in recommending movies to users.<\/jats:p>","DOI":"10.1145\/3338244","type":"journal-article","created":{"date-parts":[[2020,10,16]],"date-time":"2020-10-16T04:29:05Z","timestamp":1602822545000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":29,"title":["Predicting Users\u2019 Movie Preference and Rating Behavior from Personality and Values"],"prefix":"10.1145","volume":"10","author":[{"given":"Euna Mehnaz","family":"Khan","sequence":"first","affiliation":[{"name":"DataLab, Department of CSE, BUET, Dhaka, Bangladesh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Md. 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