Consumer’s Sentiment Analysis of Popular Phone Brands and Operating System Preference

In today‟s era, which is symbolic of „information overload‟, we are living in a time where knowledge needs to be mined from information which is available in abundance, one such instance being mining sentiments from user textual reviews which plays a decisive role in consumer‟s decision making processes. Today‟s customers are intelligent enough and will cross-check before purchasing any product and the best place for that are online reviews which are ubiquitous. In today‟s competitive market, analyzing user needs and sentiments is of uttermost importance as one bad review can make or break the profits of a brand since Word of Mouth plays a significant role in building a customer base for a brand or product. An approach for consumer‟s sentiment analysis has been proposed, which will mine user‟s sentiments and thus pave a foundation for generating the popularity of the products which will lead to „personalized‟ results which are necessary in today‟s client-centric world. This in turn is helpful for brands wanting to expand the horizon of their user turnover and to devise better retailing strategies to sell their products. The approach is to convert these textual reviews into star ratings that will describe the „likeability‟ and popularity of the products. General Terms Sentiment Analysis, Data Mining, Opinion Mining.