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Movie Title Keywords: A Text Mining and Exploratory Factor Analysis of Popular Movies in the United States and China

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  • Xingyao Xiao

    (Graduate School of Education, University of California, Berkeley, CA 94720, USA)

  • Yihong Cheng

    (Lynch School of Education and Human Development, Boston College, Chestnut Hill, MA 02467, USA)

  • Jong-Min Kim

    (Statistics Discipline, Division of Science and Mathematics, University of Minnesota-Morris, Morris, MN 56267, USA)

Abstract

Unprecedented opportunities have been brought by advancements in machine learning in the prediction of the economic success of movies. The analysis of movie title keywords is one promising but rarely investigated direction of study. To address this gap, we performed a text mining and exploratory factor analysis (EFA) of the relationships between movie titles and their corresponding movies’ levels of success. Specifically, intragroup and intergroup analyses of 217 top hit movies in the United States and 245 top hit movies in China showed that successful movies in these two major movie markets with outstanding total lifetime grosses featured titles with similar and different patterns of most frequently used words, revealing useful information about viewers’ preferences in these countries. The findings of this study will serve to better inform the movie industry in giving more economically promising names to their products from a machine-learning perspective and inspire further studies.

Suggested Citation

  • Xingyao Xiao & Yihong Cheng & Jong-Min Kim, 2021. "Movie Title Keywords: A Text Mining and Exploratory Factor Analysis of Popular Movies in the United States and China," JRFM, MDPI, vol. 14(2), pages 1-19, February.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:2:p:68-:d:494824
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    References listed on IDEAS

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    1. Fan Feng & Ravi Sharma, 2016. "Modeling the Main Determinants of Movie Sales: An Econometric Study of Chinese Marketplace," Journal of Reviews on Global Economics, Lifescience Global, vol. 5, pages 190-209.
    2. Byeng-Hee Chang & Eyun-Jung Ki, 2005. "Devising a Practical Model for Predicting Theatrical Movie Success: Focusing on the Experience Good Property," Journal of Media Economics, Taylor & Francis Journals, vol. 18(4), pages 247-269.
    3. Bae, Giwoong & Kim, Hye-jin, 2019. "The impact of movie titles on box office success," Journal of Business Research, Elsevier, vol. 103(C), pages 100-109.
    4. Legoux, Renaud & Larocque, Denis & Laporte, Sandra & Belmati, Soraya & Boquet, Thomas, 2016. "The effect of critical reviews on exhibitors' decisions: Do reviews affect the survival of a movie on screen?," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 357-374.
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    Cited by:

    1. Joshua Eklund & Jong-Min Kim, 2022. "Examining Factors That Affect Movie Gross Using Gaussian Copula Marginal Regression," Forecasting, MDPI, vol. 4(3), pages 1-14, July.

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