research-article

Predicting Users’ Movie Preference and Rating Behavior from Personality and Values

Authors:

Euna Mehnaz Khan,

Md. Saddam Hossain Mukta,

Mohammed Eunus Ali,

Jalal MahmudAuthors Info & Claims

ACM Transactions on Interactive Intelligent Systems (TiiS), Volume 10, Issue 3

Article No.: 22, Pages 1 - 25

https://doi.org/10.1145/3338244

Published: 15 October 2020 Publication History

Abstract

In this article, we propose novel techniques to predict a user’s movie genre preference and rating behavior from her psycholinguistic attributes obtained from the social media interactions. The motivation of this work comes from various psychological studies that demonstrate that psychological attributes such as personality and values can influence one’s 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’s 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.

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Chapman HAbraham A(2024)Trending Now: Implicit Factors Influence Users’ Online Audiovisual Media Motivations and EngagementImagination, Cognition and Personality10.1177/02762366241263842Online publication date: 21-Jul-2024
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Mukta MAhmad JZaman AIslam S(2024)Attention and Meta-Heuristic Based General Self-Efficacy Prediction Model From Multimodal Social Media DatasetIEEE Access10.1109/ACCESS.2024.337355812(36853-36873)Online publication date: 2024
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Mukta MAhmed JRaiaan MFahad NIslam MImtiaz NIslam MAli MAzam S(2024)Behavior Based Group Recommendation from Social Media Dataset by Using Deep Learning and Topic ModelingSN Computer Science10.1007/s42979-024-03055-15:6Online publication date: 16-Jul-2024
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Index Terms

Predicting Users’ Movie Preference and Rating Behavior from Personality and Values
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
        Supervised learning by regression
2. Information systems
  1. Information systems applications
    1. Collaborative and social computing systems and tools
      1. Social networking sites

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cover image ACM Transactions on Interactive Intelligent Systems

ACM Transactions on Interactive Intelligent Systems Volume 10, Issue 3

Special Issue on Data-Driven Personality Modeling for Intelligent Human-Computer Interaction

September 2020

189 pages

ISSN:2160-6455

EISSN:2160-6463

DOI:10.1145/3430388

Editor:
Michelle X. Zhou
Juji, Inc., USA

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Publication History

Published: 15 October 2020

Accepted: 01 August 2019

Revised: 01 July 2019

Received: 01 February 2019

Published in TIIS Volume 10, Issue 3

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https://doi.org/10.1177/02762366241263842
Mukta MAhmad JZaman AIslam S(2024)Attention and Meta-Heuristic Based General Self-Efficacy Prediction Model From Multimodal Social Media DatasetIEEE Access10.1109/ACCESS.2024.337355812(36853-36873)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3373558
Mukta MAhmed JRaiaan MFahad NIslam MImtiaz NIslam MAli MAzam S(2024)Behavior Based Group Recommendation from Social Media Dataset by Using Deep Learning and Topic ModelingSN Computer Science10.1007/s42979-024-03055-15:6Online publication date: 16-Jul-2024
https://doi.org/10.1007/s42979-024-03055-1
Preniqi VKalimeri KSaitis C(2023)Soundscapes of morality: Linking music preferences and moral values through lyrics and audioPLOS ONE10.1371/journal.pone.029440218:11(e0294402)Online publication date: 29-Nov-2023
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