A user opinion and metadata mining scheme for predicting box office performance of movies in the social network environment

Daehoon Kim, Daeyong Kim, Eenjun Hwang, Hong Gu Choi

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


With the rapid proliferation of social network services (SNS), it has become common for people to express their thoughts or opinions on various subjects, such as political events, movies, or commercial products, using short comments. Though the comments reflect personal opinion or preferences, collectively, these represent public opinion or trends. Mining public opinion or trends from a collection of user comments made on SNS could be very useful for many applications. One interesting application is to predict the box office performance of a new movie from user comments made on the movie's trailer. Such a prediction is, nevertheless, a very complicated task because many factors can have an influence on it. In this paper, we propose a scheme for mining public opinion from a collection of user comments, easily available on social networks, on the trailer of a new movie. Next, we predict whether the movie will be a box office hit, based on public opinion and other properties such as the leading actors, director, and their past works. Through various experiments, we show that our scheme can produce satisfactory results.

Original languageEnglish
Pages (from-to)259-272
Number of pages14
JournalNew Review of Hypermedia and Multimedia
Issue number3-4
Publication statusPublished - 2013 Dec 1

Bibliographical note

Funding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012-0007202) and the Ministry of Science, ICT & Future Planning (MSIP), Korea, under the Information Technology Research Center (ITRC) support program (NIPA-2013-H0301-13-3006) supervised by the NIPA (National IT Industry Promotion Agency).


  • Box office hit
  • Movie trailer
  • Public opinion
  • Social network
  • Trend

ASJC Scopus subject areas

  • Information Systems
  • Media Technology
  • Computer Science Applications


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