A Comparative Study on Sentiment Analysis Approaches and Methods

With the rapid development of Internet and its usages, Sentiment analysis, the subsidiary of Natural Language processing has also grown. Through, it the implicit emotion in the text can be powerfully mined and this information can be used by organization or enterprises to take further decisions and the unpredictable growth of data indubitably brings more opportunities and challenges to sentiment analysis. Binary Classification Problem, Data sparsely problem, polarity shift, accuracy related issues are primary problems. Multiples algorithms which are based on many approaches used for sentiment analysis, still to get the sentiment features from the particular content of text is still difficult one. In this paper provides a deep imminent of different sentiment methodologies and approaches in a comprehensive way and provide a insight of future challenges in sentiment analysis.