Date of Publication :8th March 2017

Abstract: An enormous growth of the WWW has been instrumental in spreading social networks. Due to many-fold increase in internet users taking to online reviews and opinions, the communication, sharing and collaboration through social networks have gained importance. The rapid growth in web-based activities has led to generation of huge amount of unstructured data which accounts for over 80% of the information. Exploiting big data alternatives in storing, processing, archiving and analyzing this data becomes increasingly necessary. Unstructured data refers to information that either does not have predefined data model or is not organized in a predefined manner. Unstructured data is being constantly generated via call center logs, emails, documents on the web, blogs, tweets, customer comments, customer reviews and so on. While the amount of data is increasing rapidly, the ability to summarize, understand and make sense of such data for making better decision remain challenging. So thus there is a need of sentiment analysis on unstructured data. In this paper we are describing what is sentiment analysis and methodology of analyzing on unstructured data .We have done analysis on various data sets from twitter , blogs and movielen.com site using r statistical language and output are visualized in the form of word cloud and histogram.We have created GUI’s for analysis of this datasets by which users can easily analyze the data.

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