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IJSTR >> Volume 9 - Issue 6, June 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Supervised Machine Learning For Sentiment Analysis

[Full Text]

 

AUTHOR(S)

Prashant Kumar Shrivastava

 

KEYWORDS

Sentiment Analysis, Supervised Machine Learning, SVM, KNN, Decision Tree

 

ABSTRACT

Web has been becoming a very important part in people’s life. People express their opinions and reviews related to the products and services on the web. Therefore, product reviews are generated daily on large scale. By analyzing these products reviews, new customers find others opinion. The categorization of reviews is very important for any business to grow. Broadly reviews are classified as positive or negative. Sentiment analysis is broadly applied to voice of customer materials like opinions, reviews and responses. Manufacturers or organizations become aware of good and bad things about their products, service and their competitors by analyzing sentiments from reviews of users. In order to make and maintain impression in market, every organization is continuously watching user reviews. In this paper we proposed to classify the sentiments from product reviews using supervised machine learning. Performance of Support Vector Machines (SVM), K Nearest Neighbor (KNN) and Decision Tree algorithms are compared and analyzed.

 

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