Proceedings ArticleDOI
Relationships between classical factors, social factors and box office collections
Vinay Biramane,Himanshu Kulkarni,Anand Bhave,Pranali Kosamkar +3 more
- pp 35-39
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TLDR
Predictive models are built by establishing links between classical features, social media features and the overall success of the movie which includes total box office collection and the critics rating or review, and show that the prediction model built using integration of classical as well as social factors can achieve higher accuracy rate.Abstract:
Every year the number of movie produced and released surpass the previous year's count and so do the total box office collections. So in this quality centric industry, it becomes imperative that the movie succeeds both in terms of box office collections and critical reviews and also renders profit. Due to advent of predictive analytics and big data generated through various social interactions, models to predict accurately the total gross of a movie can be devised, which eventually help the movie studio by giving constructive feedback both in pre-production and post-production phase. So the availability of this data gathered from various social platforms like IMDb, YouTube and Wikipedia can help to gauge the society's reaction and response towards a particular movie. It can also foretell a society's anticipation towards a particular movie. In this paper, we have built predictive models by establishing links between classical features, social media features and the overall success of the movie which includes total box office collection and the critics rating or review. The results show that the prediction model built using integration of classical as well as social factors can achieve higher accuracy rate.read more
Citations
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Film Box Office Forecasting Methods Based on Partial Least Squares Regression Model
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Prediction of IMDB Movie Score & Movie Success By Using The Facebook
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TL;DR: In this article , a predictive model is developed that exploits Facebook features to predict movie success and IMDB score and SVM shows the 84% accuracy in the prediction of movie success in terms of Hit and Flop; hence conclusion drawn is that the sentiment score of Facebook page will improve the accuracy of prediction model for movie success.
References
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Proceedings Article
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