Movie Success Forecast and Revenue Prediction Using Fuzzy System

Abstract

Social media has grown ubiquitous and indispensable for social networking and content sharing in recent years. Despite this, the content supplied by these websites is generally unexplored by government officials. The current tutorial looks at social media modelling, analytics, and optimization approaches. First, we'll go over how to acquire massive amounts of social media data, then we'll go over how to deal with and adjust for the consequences of missing or incomplete data. We explain how social media material may be utilised to predict real-world consequences in this study. We utilise Twitter.com buzz in particular to anticipate box-office revenues for movies. We demonstrate that a simple model based on the pace at which tweets regarding specific subjects are produced may surpass market-based estimations. We also show how emotions derived from Twitter may be used to improve social media's predicting capabilities. We present the results of a study that used Twitter data to forecast box office receipts. An increase in the number of tweets about a movie before its premiere is thought to result in higher box office revenue.