The evolution of Social Networks, Blogs and Online reviews lead to enormous amounts of user generated opinions related to feedback, perspectives, ratings and recommendations about products, places, events, movies, etc. This led to ‘Sentiment Analysis (SA)’ which is study of sentiments from the user generated data. These sentiments help in better decision making. SA received great interest due to its plethora of applications in Business Systems, Marketing, Politics to analyse the trend of the public towards a political party, mining the online-social media for analysing the content, and in promotion of e-Business by analysing the customers.

Sentiment Analysis deals with Computational linguistics i.e. Natural Language Processing (NLP) of streams of data in generated in different languages (Sundry Corpora-Telugu Language). Various approaches are implemented to predict the sentiments of words, sentences or documents automatically. These approaches involve NLP and pattern-recognition based semantic techniques.  Identifying a sentiment involves understanding the constructs of the natural language like sentences, words used in the context, rules, pre & post scenarios, etc.