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Reseach Article

A Supervised Learning Technique for Classifying Amazon Product Reviews based on Buyers Sentiments

by Richa Chunekar Kokje, Gajendra Singh Chouhan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 38
Year of Publication: 2020
Authors: Richa Chunekar Kokje, Gajendra Singh Chouhan
10.5120/ijca2020920956

Richa Chunekar Kokje, Gajendra Singh Chouhan . A Supervised Learning Technique for Classifying Amazon Product Reviews based on Buyers Sentiments. International Journal of Computer Applications. 175, 38 ( Dec 2020), 36-41. DOI=10.5120/ijca2020920956

@article{ 10.5120/ijca2020920956,
author = { Richa Chunekar Kokje, Gajendra Singh Chouhan },
title = { A Supervised Learning Technique for Classifying Amazon Product Reviews based on Buyers Sentiments },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2020 },
volume = { 175 },
number = { 38 },
month = { Dec },
year = { 2020 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number38/31703-2020920956/ },
doi = { 10.5120/ijca2020920956 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:40:38.945515+05:30
%A Richa Chunekar Kokje
%A Gajendra Singh Chouhan
%T A Supervised Learning Technique for Classifying Amazon Product Reviews based on Buyers Sentiments
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 38
%P 36-41
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A number of applications using internet provide vary essential services. Among them social media and ecommerce platforms are very common. These platforms include a large amount of data which is generated by the users. That data is available in the form of opinion about some post or review. Means the text with emotions which is contain the buyers or user sentiment about some kind of product or service. In this presented work a data mining model is introduced that offers sentiment based text classification for the Amazon product reviews. The proposed data model first preprocesses data and extract the actual review text, in next phase of preprocess the stop words and special characters are removed. The refined text is further utilized with two feature selection techniques first is based on TF-IDF which is used for selecting intense keywords from the review text. Additionally the second feature is selected using NLP text parser. That parser basically performs the POS (Part Of Speech) tagging of review text. Using the obtained POS tags the NLP feature is contracted. Both the features are combined in next and two supervised learners are used namely SVM (support vector machine) and SVR (support vector regression). The experimental results of both the model is measured and compared. The performance study demonstrates the proposed SVM based classifier performs classification accurately and efficiently as compared to SVR based classifier.

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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment analysis text classification NLP Amazon product review hidden emotions on text.