Sentiment analysis: Approaches and open issues

Abstract

Sentiment Analysis is the process which helps to identify and classifying the opinions or feelings expressed in opinioned data, in order to ascertain whether the attitude of the writer towards a particular service, product etc. is negative, positive or neutral. Sentiment analysis also helps the consumers to identify if the information in the neighborhood of the product or service is satisfactory or not before the customers buy it. The interest of the scientific communities and business world is increasing day by day to gather, process and extract the knowledge from the public opinions available on different types of social media. The main problems that exist in the current techniques are: inability to perform well in different domains, inadequate accuracy and performance in sentiment analysis based on insufficient labeled data, incapability to deal with complex sentences that require more than sentiment words and simple analyzing. This article discusses the different approaches for sentiment analysis and open problems and issues present in performing sentiment analysis.