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Classifying Movies Based on Audience Perceptions: MTI Framework and Box Office Performance

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  • Ji-Hyun Shon
  • Young-Gul Kim
  • Sang-Jin Yim

Abstract

This research examined the current status of the movie genre usage in movie research and film industry and introduced a new method to classify movies. Using a large-scale audience survey data, the authors clustered movies into 9 distinct types based on 8 audience-perceived movie characteristics such as fun, eye-catching, discomfort, and feel-good. The authors validated their method by comparing movie types vs. movie genres in terms of their box-office revenue explanatory power. All three types of box-office revenues (opening week revenue, total revenue, revenue-per-screen) differed significantly across movie types, whereas only the opening week revenue showed a significant difference across movie genres, suggesting that movie types may be a better predictor of a movie's box-office performance than movie genres that have been frequently used in prior research on box-office performance prediction.

Suggested Citation

  • Ji-Hyun Shon & Young-Gul Kim & Sang-Jin Yim, 2014. "Classifying Movies Based on Audience Perceptions: MTI Framework and Box Office Performance," Journal of Media Economics, Taylor & Francis Journals, vol. 27(2), pages 79-106, June.
    • Handle: RePEc:taf:jmedec:v:27:y:2014:i:2:p:79-106
    DOI: 10.1080/08997764.2014.903959
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    Cited by:

    1. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.

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