Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data

Márton Mestyán, Taha Yasseri and János Kertész

PLOS ONE, 2013, vol. 8, issue 8, 1-8

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.

Date: 2013
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Citations: View citations in EconPapers (35)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0071226

DOI: 10.1371/journal.pone.0071226

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