Product opinion mining using sentiment analysis on smartphone reviews

An unexpected increase in the application of social web sites has led to the need in development of a very robustful and trust worthy systems and varied machinery forms in order to analyze such large forms of data and their ware houses which is being collected from various industries. We are always eager and excited to know what people think what they feel and perceive about various aspects of living and non-living beings. In need to understand and analyze various traits of behavior and the varying personality there is a need of opinion mining. It is a collection of all the extracted information from all the available resources and possible instances which could be in the form of hidden emotions, paragraphs and could be text, urban language and various un-identified representations. It is not only related topics like sensex, politics, finance and other meaningful words, but represents many things in the wide area of application. Almost all the sites have provided the option to display and present various medias and their views on various real life events. They can share various aspects of philosophy too and many more. They can represent various opinions on various streams of life which has really become crucial in our daily life to analyze the pattern in which things are exponentially growing. This research paper provides you with sentimental analysis of various smart phone opinions on smart phones dividing them Positive, Negative and Neutral Behavior. This is basically being obtained by studying the various posts being posted by varied number of users considering their areas of interest categorizing the smart phones. Analysis of plenty of words coupled in a sentence represent various sentiments of users and the various experiences and impact that product has given them. This analysis compiles a structural modeling approach and Bayesian Interface system to identify the polarity of the opinion which subsequently classifies positive and negative opinions.