Twitter Popularity v/s Yelp Ratings: Predictive and Sentiment Analysis of Food Chains

Computer Engineering

Yelp connects people to great local businesses. Twitter is another important social media portal where twitter users express their experiences in a few sentences called tweets. This paper, focus on the reviews for restaurants. This model predict the star ratings for the restaurant from the Tweets extracted from Twitter. Through current work here, this paper perform a predictive analysis between the Yelp ratings of among popular food chains vs their equivalent twitter recommendations. Three machine learning algorithms are used with the sentiment analysis. After analyzed the performance of each models, the best model for predicting the ratings from reviews is the Naïve Bayes algorithm. Also, found that sentiment features are very useful for rating prediction.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.