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Feature Selection and Classification for Sentiment Analysisof Amazon Product Reviews

Smita Suresh Daniel1 , Ani Thomas2 , Neelam Sahu3

Section:Review Paper, Product Type: Journal Paper
Volume-07 , Issue-03 , Page no. 173-177, Feb-2019

Online published on Feb 15, 2019

Copyright © Smita Suresh Daniel, Ani Thomas, Neelam Sahu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Smita Suresh Daniel, Ani Thomas, Neelam Sahu, “Feature Selection and Classification for Sentiment Analysisof Amazon Product Reviews,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.173-177, 2019.

MLA Style Citation: Smita Suresh Daniel, Ani Thomas, Neelam Sahu "Feature Selection and Classification for Sentiment Analysisof Amazon Product Reviews." International Journal of Computer Sciences and Engineering 07.03 (2019): 173-177.

APA Style Citation: Smita Suresh Daniel, Ani Thomas, Neelam Sahu, (2019). Feature Selection and Classification for Sentiment Analysisof Amazon Product Reviews. International Journal of Computer Sciences and Engineering, 07(03), 173-177.

BibTex Style Citation:
@article{Daniel_2019,
author = {Smita Suresh Daniel, Ani Thomas, Neelam Sahu},
title = {Feature Selection and Classification for Sentiment Analysisof Amazon Product Reviews},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {07},
Issue = {03},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {173-177},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=702},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=702
TI - Feature Selection and Classification for Sentiment Analysisof Amazon Product Reviews
T2 - International Journal of Computer Sciences and Engineering
AU - Smita Suresh Daniel, Ani Thomas, Neelam Sahu
PY - 2019
DA - 2019/02/15
PB - IJCSE, Indore, INDIA
SP - 173-177
IS - 03
VL - 07
SN - 2347-2693
ER -

           

Abstract

Online reviews provide accessible and plentiful data for relatively easy analysis for a given product.This paper seeks to apply and extend the current work in the field of Natural Language processing and sentiment analysis to retrieve information from Amazon Product reviews classify them using Naïve bayes classifier . This work presents a methodology that shows how text data can provide insight into various features of a product found in the customer reviews and feature selection method.

Key-Words / Index Term

Feature selection , Sentiment classification, Categorization

References

[1] Y. Yang and J.O Pedersen, “A Comparative study on Feature Selection in Text Categorization “,In International Conference on Machine Learning (ICML), 1997.
[2] L. Dey, S. Chakraborty, A. Biswas, B. Bose, and S. Tiwari, “Sentiment analysis of Review Datasets using Naïve Bayes’ and k-NN Classifiers.” ,Int. J. of Information Engineering and Electronic Business,vol. 4, pp. 54-62, 2016.
[3] I. Hemalatha , G. P Saradhi V., &A. Govardhan, “Preprocessing the Informal Text for efficient Sentiment Analysis” , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS),Volume 1, Issue 2,2012.
[4] Wei Gao , Fabrizio Sebastiani ,” TweetSentiment: From Classification to Quantification’,Springer-Verlag Wien 2016
[5] M. Bouazizi and T. Ohtsuki, ‘‘Sentiment analysis in Twitter: Fromclassification to quantification of sentiments within tweets,’’ inProc. IEEEGLOBECOM, Dec. 2016, pp. 1–6.
[6] Aashutosh Bhatt, Ankit Patel, Harsh Chheda, Kiran Gawande,” Amazon Review Classification and SentimentAnalysis”, International Journal of Computer Science and Information Technologies, Vol. 6 (6) , 2015, 5107-5110