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Early prediction of movie box office success based on Wikipedia activity big data.

ABSTRACT: Use of socially generated "big data" to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between "real time monitoring" and "early predicting" remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.

SUBMITTER: Mestyan M

PROVIDER: S-EPMC3749192 | biostudies-other | 2013

REPOSITORIES: biostudies-other

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Early prediction of movie box office success based on Wikipedia activity big data.

Mestyán Márton M Yasseri Taha T Kertész János J

PloS one 20130821 8

Use of socially generated "big data" to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between "real time monitoring" and "early predicting" remains a big challenge. Here we report on an endeavor to build a minimalistic pr ...[more]

PMID: 23990938

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