Sentiment Classification through Semantic Orientation Using SentiWordNet
نویسندگان
چکیده
Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease in making choices regards to online shopping, choosing events, products, entities. In this paper, a rule based domain independent sentiment analysis method is proposed. The proposed method classifies subjective and objective sentences from reviews and blog comments. The semantic score of subjective sentences is extracted from SentiWordNet to calculate their polarity as positive, negative or neutral based on the contextual sentence structure. The results show the effectiveness of the proposed method and it outperforms the machine learning methods. The proposed method achieves an accuracy of 87% at the feedback level and 83% at the sentence level for comments. [Aurangzeb khan, Muhammad Zubair Asghar, Shakeel Ahmad, Fazal Masud Kundi, Maria Qasim, Furqan. Sentiment Classification through Semantic Orientation Using SentiWordNet. Life Sci J 2014; 11(10):309-315] (ISSN: 1097-8135). http://www.lifesciencesite.com. 44
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