A Novel Approach for Interpreting Public Sentiment Variations on Twitter: A Review

With the explosive growth of user generated messages, Twitter has become a social site where millions of users can exchange their opinion. Sentiment analysis on Twitter data has provided an economical and effective way to expose public opinion timely, which is critical for decision making in various domains. Similarly, due to the large volume of opinion rich web resources such as discussion forum, review sites, blogs and news corpora available in digital form, much of the current research is focusing on the area of sentiment analysis. Because this information is very useful for businesses, governments and individuals. While this content meant to be helpful analysing this bulk of user generated content is difficult and time consuming. So there is a need to develop an intelligent system which automatically mine such huge content and classify them into positive, negative and neutral type. Sentiment analysis is the automated mining of attitudes, opinions, and emotions from text, and database sources through Natural Language Processing (NLP). The objective of this paper is to discover the concept of Sentiment Analysis and Sentiment Variations in the field of Natural Language Processing and presents a study of its techniques in this field.