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Rapid increase in internet users along with growing power of online reviewsites and social media has given birth to sentiment analysis or opinion mining,which aims at determining what other people think and comment. Sentiments orOpinions contain public generated content about products, services, policiesand politics. People are usually interested to seek positive and negativeopinions containing likes and dislikes, shared by users for features ofparticular product or service. This paper proposed sentence-level lexical baseddomain independent sentiment classification method for different types of datasuch as reviews and blogs. The proposed method is based on general lexiconsi.e. WordNet, SentiWordNet and user defined lexical dictionaries for semanticorientation. The relations and glosses of these dictionaries provide solutionto the domain portability problem. The method performs better than word andtext level corpus based machine learning methods for semantic orientation. Theresults show the proposed method performs better as it shows precision of 87%and83% at document and sentence levels respectively for online comments.

Lexical Based Semantic Orientation of Online Customer Reviews and Blogs