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Sentiment Analysis on Product Reviews using Hadoop

by Jalpa Mehta, Jayesh Patil, Rutesh Patil, Mansi Somani, Sheel Varma
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 11
Year of Publication: 2016
Authors: Jalpa Mehta, Jayesh Patil, Rutesh Patil, Mansi Somani, Sheel Varma
10.5120/ijca2016909892

Jalpa Mehta, Jayesh Patil, Rutesh Patil, Mansi Somani, Sheel Varma . Sentiment Analysis on Product Reviews using Hadoop. International Journal of Computer Applications. 142, 11 ( May 2016), 38-41. DOI=10.5120/ijca2016909892

@article{ 10.5120/ijca2016909892,
author = { Jalpa Mehta, Jayesh Patil, Rutesh Patil, Mansi Somani, Sheel Varma },
title = { Sentiment Analysis on Product Reviews using Hadoop },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 11 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 38-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number11/24942-2016909892/ },
doi = { 10.5120/ijca2016909892 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:44:44.511238+05:30
%A Jalpa Mehta
%A Jayesh Patil
%A Rutesh Patil
%A Mansi Somani
%A Sheel Varma
%T Sentiment Analysis on Product Reviews using Hadoop
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 11
%P 38-41
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Most of the e-commerce sites ask their customers to provide relevant reviews on their products which could help other customers to decide their choice. A slew of reviews is being generated on a daily basis due to an increase in the usage of e-commerce sites. A potential customer may need to go through thousands of reviews before arriving at a firm decision, which is time-consuming. The project elaborated below aims at reducing this time constraint, by providing an effective summarization of reviews in a manner suitable for users. Usage of MapReduce technique provided by Apache Hadoop is highly emphasized for processing reviews. The summarization of reviews is limited to attributes that the potential customers might be interested while looking for the particular product. In this paper, the technique used for the same is described which substantially reduces time complexity when implemented.

References
  1. S. Chandrakala and C. Sindhu. “Opinion Mining and Sentiment Classification: A Survey” ICTACT Journal on Soft Computing, October 2012, Volume: 03, issue: 01, ISSN: 2229-6956.
  2. Yun Niu, MSc, Xiaodan Zhu, MSc, Jianhua Li, MSc and Graeme Hirst, PHD. “Analysis of Polarity Information in Medical Text” AMIA 2005 Symposium.
  3. Nidhi Mishra, C. K. Jha, PHD. “Classification of Opinion Mining Techniques”. International Journal of Computer Applications (0975 – 8887), Volume 56– no.13, October 2012.
  4. Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. “Sentiwordnet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining” LREC 2010.
  5. Mrigank Mridul, Akashdeep Khajuria, Snehasish Dutta, Kumar N, Prasad. M. R., “Analysis of Big Data using Apache Hadoop and Map Reduce” Volume 4, Issue 5, May 2014, India.
  6. Minqing Hu and Bing Liu, “Mining Opinion Features in Customer Reviews”, American Association for Artificial Intelligence, 2004.
  7. Othman Yahya, Osman Hegazy, Ehab Ezat, “An Efficient Implementation Of Apriori Algorithm Based On Hadoop - MapReduce Model”, International Journal of Reviews in Computing, ISSN: 2076-3328.
  8. Kushal Dave, Steve Lawrence, David M. Pennock, “Mining the Peanut Gallery: Opinion Extraction and Semantic Classification of Product Reviews”, ACM 2003.
  9. Kavita Ganesan, ChengXiang Zhai & Evelyne Viegas. “Micropinion Generation: An Unsupervised Approach to Generating Ultra-Concise Summaries of Opinions” (2012) Lyon, France, April 16–20.
  10. Tingting Wei, Yonghe Lu c, Huiyou Chang, Qiang Zhou, Xianyu Bao “A semantic approach for text clustering using WordNet and lexical chains” (2014) China, 18 October.
  11. Sinno Jialin Pany, Xiaochuan Niz, Jian-Tao Sunz, Qiang Yangy and Zheng Chen (2010) North Carolina, USA, April 26–30. “Cross-Domain Sentiment Classification via Spectral Feature Alignment”.
  12. Mrigank Mridul, Akashdeep Khajuria, Snehasish Dutta, Kumar N, Prasad .M .R “Analysis of Bidgata using Apache Hadoop and Map Reduce” Volume 4, Issue 5, May 2014, India.
Index Terms

Computer Science
Information Sciences

Keywords

Sentiment Analysis Opinion Mining Product Reviews Hadoop MapReduce OpenNLP SentiWordNet.

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