Difference between revisions of "Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data"

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'''Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data''' - scientific work related to Wikipedia quality published in 2013, written by Márton Mestyán, Taha Yasseri, Taha Yasseri, Taha Yasseri, János Kertész, János Kertész and János Kertész.
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'''Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Márton Mestyán]], [[Taha Yasseri]], [[Taha Yasseri]], [[Taha Yasseri]], [[János Kertész]], [[János Kertész]] and [[János Kertész]].
  
 
== Overview ==
 
== Overview ==
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 authors report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. Authors 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.
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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 authors report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. Authors 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.

Revision as of 05:59, 22 July 2019

Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data - scientific work related to Wikipedia quality published in 2013, written by Márton Mestyán, Taha Yasseri, Taha Yasseri, Taha Yasseri, János Kertész, János Kertész and János Kertész.

Overview

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 authors report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. Authors 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.