Analysis Of Sentiment In User Reviews And Twitter Data To Predict Vehicle Sales

Abstract

Because of the growth of social media, writing comments or expressing thoughts on products online is now simpler than ever. Data from user evaluations might be one of the most important sources for anticipating vehicle sales. Sentiment Analysis is another way to understand if the user is satisfied with the product which will help the manufacturer to improve the features in the upcoming release. User reviews play a vital role in analysis and predict which product will have much production and sales in future. In this paper a set of algorithms are used to predict the sentiment analysis including the Naive Bayes, Logistic Regression and Random Forest Classifier. The categorization and prediction will be based on user-defined reviews and data from Twitter.