Sentiment Analysis |
Author(s): |
| Prof. Reena Mahe , Atharva College of Engineering University of Mumbai, India; Prof. Sumita Chandak, Atharva College of Engineering University of Mumbai, India; Prof. Nileema Pathak, Atharva College of Engineering University of Mumbai, India; Prof. Renuka Nagpure, Atharva College of Engineering University of Mumbai, India; Prof. K. Tejaswi, Atharva College of Engineering University of Mumbai, India |
Keywords: |
| Reviews, Polarity, Sentiment Analysis, Sentence Level, Document Level, Feature Level |
Abstract |
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With the evolution of web technology and social media, online shopping has become very famous as it is convenient, easy and time saving. It also provides platform to share experiences and provide feedback. These reviews help to know whether the product is good or bad and to make decisions by potential customers. Sentiment analysis is the method by which information can be fetched from these reviews, analyzed and categorized as positive, negative or neutral. Main purpose of Sentiment analysis is to train computers to be able to understand, recognize and generate emotions. The other names for sentiment analysis are Opinion Mining, Opinion Extraction, Sentiment Mining and Subjective Analysis. Different challenges in this process, methods and levels on which sentiment analysis can be performed are discussed in this paper. |
Other Details |
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Paper ID: NCTAAP049 Published in: Conference 4 : NCTAA 2016 Publication Date: 29/01/2016 Page(s): 210-213 |
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