Social Media is the next logical marketing arena. Currently, Social networking sites dominate the digital marketing space. In the past years, the World Wide Web (WWW) has become a huge source of user-generated content and opinionative data. Using social media, such as Twitter, facebook, etc, user shares their views, feelings in a convenient way. Social media, where millions of people express their views in their daily interaction, provides their sentiments and opinions about particular thing. A lot of work done earlier analyzes the polarity from text but the accuracy of existing technique is not acceptable because of the lack of feature optimization selection. The concept of feature optimization is used to find out the relevant data according to the sentiment classes. By using the concept of feature optimization technique, the chances of removal of irrelevant data is more and we can achieve better accuracy. In the proposed work, a classification technique named as Artificial Neural Network (ANN) along with genetic algorithm, an optimization algorithm will be used and it can train the large amount of dataset that is optimized by using Genetic Algorithm (GA) approach and can be divided into their groups according to the feature for social sentiment database.

Data mining, Genetic algorithm, ANN,ARM

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