Role of Different Factors in Predicting Movie Success

被引：0

作者：

Bhave, Anand ^{[1
]}

Kulkarni, Himanshu ^{[1
]}

Biramane, Vinay ^{[1
]}

Kosamkar, Pranali ^{[1
]}

机构：

[1] MIT, Dept Comp Engn, Pune, Maharashtra, India

来源：

2015 INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING (ICPC) | 2015年

关键词：

Box office; Forecasting; Gross income; Machine learning; Movie success; Movie; Predictive analytics;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Due to rapid digitization and emergence of social media the movie industry is growing by leaps and bounds. The average number of movies produced per year is greater than 1000. So to make the movie profitable, it becomes a matter of concern that the movie succeeds. Given the low success rate, models and mechanisms to predict reliably the ranking and or box office collections of a movie can help de-risk the business significantly and increase average returns. The current predictive models available are based on various factors for assessment of the movie. These include the classical factors such as cast, producer, director etc. or the social factors in form of response of the society on various online platforms. This methodology lacks to harvest the required accuracy level. Our paper suggests that the integration of both the classical and the social factors (anticipation and user feedback) and the study of interrelation among the classical factors will lead to more accuracy.

引用

页数：4