Sentiment Analysis of E-commerce Product Review through Machine Learning

Abstract

Sentiment analysis is a way which is used to determine that a piece of information is positive, negative or neutral. In the analysis of text or any kind of information natural language processing (NLP) and machine learning (ML) both are combined to assign sentiment scores to the topics, categories and any kind of entities within a given phrase. In today's day and time online shopping has become well received among the people. If we talk about ordinary people, they always think too much before buying any product through any e-commerce application. The trust of the people of e-commerce applications is not very high. So, people turn to reviews to fill this confidence gap. And to ensure this trust Sentiment Analysis were used. Our project can be a great option for people to maintain their trust. In this project we are analyzing products of respective e-commerce apps on the behalf of their reviews and ratings. Users will get information for each product whether it can be a good one or not on the basis of reviews and ratings. A great number of internet sources are present on categorical views of activities, goods and services, beliefs or perhaps the mind created by the online dwellers. In this fierce business world, various industries, especially e-commerce, exceptionally use sentiment analysis to increase productivity and make better business decisions. This project tackles a comprehensive overview of sentiment analysis and relevant techniques in the e-commerce sector that is always keen to find out about the consumers' opinions of their goods and services. It starts with the view of an assessment of sentiments that have come out as a method for understanding clients’ emotions.