OPINION MINING FOR AUTOMATED RESTAURANT REVIEWS RATING

Abstract

The objective of this project is to develop Automated Restaurant Reviews Rating Web Application. This report includes methodology and technique for opinion mining. Shortly, we are working on public opinions by doing several processing of sentiment gathered from different restaurant websites/facebook pages. Finally the end product of the processing and sentiment analysis will be in the form of web application ! In recent years, sentiment analysis became a growing trend in research area; social media gets daily bases numbers of reviews by customers of restaurants which are unable to decide whether good or worst by reading all the reviews, so that an automated system is needed to get customer reaction and give feedback as a rating or score. Processing natural language and understanding customer mind is a big challenge. Many techniques has been used in past years but still it’s a hot topic due to a single negation word can change the meaning context. We have used supervised leaning approach with negation transformation technique on Facebook live reviews data and achieved good performance other than previous researches.