Sentiment Analysis using Natural Language Processing

Sentiment analysis is the area of study which analyzes people’s opinions, sentiments, appraisals, evaluation, emotions, and attitudes towards particular entities such as organizations, individual, product, issues, events, topics, and their attributes. Sentiment analysis is a part of a natural language processing where we understanding the idea and opinion of the public about a particular things or topic. It represents a huge problem space. It involves in classifying a system to assemble opinion and then examine about the product made in blog posts, comments or tweets. Recently in some years, industrial activities surrounding sentiment analysis have also thrived. Continuously startups have been emerged. Many large corporations have made their own in-house capabilities. Sentiment analysis can be useful in several ways. There are also many names and slightly different tasks, e.g., sentiment analysis, opinion mining, opinion extraction, sentiment mining, subjectivity analysis, affect analysis, emotion analysis, review mining, etc. In fact, sentiment analysis has spread from computer science to management sciences, social sciences and in also various fields due to its importance to business and society as a whole. Sentiment analysis systems have found their applications in almost every domain either in business or in social platform. The main aim of this report is to provide a brief introduction to this fascinating problem and also to present a framework which helps in performing sentiment analysis on online mobile phone review and in different devices by associating particular algorithm.