Title

Predicting Movie Ratings using Sentiment Analysis of Tweets

Document Type

Conference Proceeding

Publication Date

4-30-2017

Publication Title

Proceedings of the Midwest Decision Science Institute Annual Conference

Abstract

Twitter is a social media platform used by millions of people across the world to share their views, opinions, and preferences on different issues. Twitter generates a huge amount of data which are represented as limited-length text in free format known as Tweets. The tweets provide big data of public opinion about movies, products or services. It is therefore necessary to develop sentiment predication methods to better understand customers and improve service delivery. This study aims to analyze and evaluate the opinions expressed about movies on Twitter. A framework of using tweets to predicting movies’ ratings is proposed in this study. A prototype based on the framework is implemented in R Studio which gives easy access to tweets used for sentiment analysis. The preliminary study sheds light on using sentiments analysis to predicting movies’ ratings.

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