Measuring Audience Sentiments about Movies using Twitter and Text Analytics


Introduction

The practice of using analytics to measure movie’s success is not a new phenomenon. Most of these predictive models are based on structured data with input variables such as Cost of Production, Genre of the Movie, Actor, Director, Production House, Marketing expenditure, no of distribution platforms, etc.

However, with the advent of social media platforms, young demographics, digital media and the increasing adoption of platforms like Twitter, Facebook, etc to express views and opinions. Social Media has become a potent tool to measure Audience Sentiments about a movie.

This report is an attempt to understand one such platform, i.e., Twitter. The movie chosen is Rangoon, which is a 2017 Bollywood movie, directed by Vishal Bhardwaj and produced by Sajid Nadiadwala and Viacom 18 Motion Pictures. The lead actors are Saif Ali Khan, Shahid Kapoor and Kangana Ranaut. The film was released on 24 February 2017 in India on a weekend.

I will be using R, an open source statistical programming tool, to carry out the analysis.

Note: I will focus on the approach and the findings. The R Code to carry out the analysis can be found at the end of the article.

 

Table of Contents

  1. Introduction to Text Analytics
  2. Objective of the Analysis
  3. Data for the Analysis
  4. Conducting the analysis ­ Approach 1 ­ using the ‘tm’ package
  5. Conducting the analysis ­ Approach 2 ­ using the ‘suazyhet’ package
  6. Conclusion
  7. Making a Prediction Algorithm for Movie Success

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