Accumulating Sentiments from Product Reviews

Abstract

Sentiment analysis at the intrinsic level refers to the study of people’s opinions, emotions, and attitudes expressed in text form. A critical reason for the lack of this study previously was the lack of opinionated text in digital form. We have been witnessing a huge explosion of sentiment-rich data in social media in the form of tweets, blog posts, status updates, forums for discussions, comments, etc. In getting the opinion of the crowd, user-generated data is very useful. The knowledge base method and machine learning technique are two strategies for analyzing sentiments. In our research, we use a Logistic Regression algorithm to analyze sentiment in product reviews. In order to make a purchase decision, people read the reviews of products before purchasing them. Our model can be used by organizations to measure customer opinions and perceptions, which can be enhanced to varying degrees based on the data collected.