The Analysis and Implementation of Film Decision-Making Based on Python

Abstract

With the growing development of the era of big data, data acquisition and analysis have become hot spots, and Python-based crawler technology is one of the most widely used tools in data analysis work at present. In this paper, we apply Python crawler key technology to acquire data of movie list and hot movies on Cat’s Eye movie network, analyze data based on Python development environment Spyder, use the Numpy system to store and process large data, Chinese Jieba word separation tool to crawl data for word separation text processing, Snownlp library to process text sentiment, and finally by the word cloud map and web dynamic map display information such as viewers’ emotional tendency and movie rating statistics, and provide decision support for users’ movie viewing.

Towards Data-Driven Decision-Making in the Korean Film Industry: An XAI Model for Box Office Analysis Using Dimension Reduction, Clustering, and Classification

“…The use of DDDM models in the film industry can also help ensure the industry’s steady growth [ 24 , 25 ]. By providing business decision support and guidance for filmmakers and distributors, DDDM models can help increase the chances of their project’s success, drive the industry’s continued growth, and ensure its long-term success [ 26 ].…”