Paper Title
Sentiment Analysis of Product Reviews using Machine Learning Approaches

Sentiment analysis is the process of determining whether the text data or sentence is positive, negative or neutral. Sentiment analysis is done with the help of natural language processing (NLP), text analysis and machine learning techniques [1]. Machine learning is a part of artificial intelligence which studies the computer algorithms that improve automatically with the help of experience and the data [2]. Natural Language Processing (NLP) is the part of artificial intelligence that studies how computers interact with human language [3]. The main aim of sentiment analysis is to identifying polarity of the text or sentence within the Web and classifying them. Therefore, to seek out polarity or sentiment of users or customer there's a requirement for automated data analysis techniques. In WWW, where many people express their views in their daily interaction, either within the social media or in e-commence which may be their sentiments and opinions about particular thing. We are scraping users reviews data from the websites in csv format as E-commerce websites permits web scraping. We applied naïve bayes and logistic regression machine learning algorithms to classify reviews that are positive, negative or neutral. In previous papers data is taken from only one website but we have taken data from multiple websites which helps to understand the better polarity. Keywords - Sentiment Analysis, Artificial Intelligence, Natural Language Processing, Naïve Bayes, Logistic Regression, Machine Learning