A Comparative Study on Classification Algorithms for Sentiment Analysis |
Author(s): |
| Vrunda Joshi , Noble Group Of Institutions Junagadh-362310; Dr. Vipul Vekariya, Noble Group Of Institutions Junagadh-362310 |
Keywords: |
| Sentient Analysis, Support Vector Machine, K-Nearest Neighbor, Artificial Neural Networks |
Abstract |
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Social media is a very popular way of expressing opinions and integrating with other people in the online world. How to analyze user generated reviews and to classify them into different sentiment classes is gradually becoming a question that people play close attention to. This problem has become a comparison benchmark test for different classification methods. Sentiment analysis focused on social networks, product reviews, stock market, news comments, etc. In this paper, I survey the various algorithms available for sentiment analysis. Different algorithms are use like Support Vector Machine, K-Nearest Neighbor, Artificial Neural Networks, etc. Sentiment analysis is used in politics, to detect stock, to add or nix the advertisements. |
Other Details |
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Paper ID: IJSRDV4I100039 Published in: Volume : 4, Issue : 10 Publication Date: 01/01/2017 Page(s): 428-430 |
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