CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
Reseach Article

A Review on Opinion Mining and Sentiment Analysis

Published on June 2016 by Tahura Shaikh, Deepa Deshpande
National Conference on Recent Trends in Computer Science and Information Technology
Foundation of Computer Science USA
NCRTCSIT2016 - Number 2
June 2016
Authors: Tahura Shaikh, Deepa Deshpande
3e8caa58-9bbc-4f49-8276-f81e18ea4b67

Tahura Shaikh, Deepa Deshpande . A Review on Opinion Mining and Sentiment Analysis. National Conference on Recent Trends in Computer Science and Information Technology. NCRTCSIT2016, 2 (June 2016), 6-9.

@article{
author = { Tahura Shaikh, Deepa Deshpande },
title = { A Review on Opinion Mining and Sentiment Analysis },
journal = { National Conference on Recent Trends in Computer Science and Information Technology },
issue_date = { June 2016 },
volume = { NCRTCSIT2016 },
number = { 2 },
month = { June },
year = { 2016 },
issn = 0975-8887,
pages = { 6-9 },
numpages = 4,
url = { /proceedings/ncrtcsit2016/number2/25023-1647/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Recent Trends in Computer Science and Information Technology
%A Tahura Shaikh
%A Deepa Deshpande
%T A Review on Opinion Mining and Sentiment Analysis
%J National Conference on Recent Trends in Computer Science and Information Technology
%@ 0975-8887
%V NCRTCSIT2016
%N 2
%P 6-9
%D 2016
%I International Journal of Computer Applications
Abstract

Opinion Mining or Sentiment Analysis is a field of data mining. Opinion Mining is a form of Natural Language Processing which is used to record the attitude of people towards a particular subject or product. Mainly Opinion Mining classifies the given review as positive, neutral or negative. Recently Opinion Mining has accomplished much focus due to availability of vast amount of opinion rich web resources in digital form such as discussion forums, review sites, blogs etc. As the use of e-commerce websites is increasing profusely, users not only buy a product on websites but also give their feedback and suggestions that will be beneficial to other users. The collected user reviews are examined, analyzed and organized to make better decision. The paper reviews the recent research work carried out in the area of opinion mining. It also outlines framework and the steps which are carried out in opinion mining. There are distinct kind of Opinion Mining such as sentence level, document level, and aspect or feature level. It aids consumers in better decision making. For a business it helps to predict brand perception, reputation management, and new product perception. An Organization gets to know their manufacture from perspective of end user. An Opinion can be direct opinion or comparative opinion. Different Machine Learning algorithms like Naïve Bayes, SVM, ANN, Maximum Likelihood, and Decision Tree are used for various tasks which are carried out in sentiment analysis.

References
  1. J. Ashok Kumar1, S. Abirami, 2015,"An Experimental Study Of Feature Extraction Techniques In Opinion Mining", International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), Vol. 4, No. 1.
  2. Lisette García-Moya, Henry Anaya-Sánchez, and Rafael Berlanga-Llavori, 2013,"Retrieving Product Features and Opinions from Customer Reviews", Intelligent Systems, IEEE ,Volume:28 , Issue: 3
  3. Su Su Htay and Khin Thidar Lynn, 2013,"Extracting Product Features and Opinion Words Using Pattern Knowledge in Customer Reviews", Hindawi Publishing Corporation, The Scientific World Journal, Volume 2013, Article ID 394758
  4. Richa Sharma,Shweta Nigam and Rekha Jain, 2014,"Mining Of Product Reviews At Aspect Level", International Journal in Foundations of Computer Science & Technology , Vol. 4, No. 3.
  5. Dim En Nyaung, Thin Lai Lai Thein, 2014,"Feature Based Summarizing From Customer Reviews", International Journal Of Scientific Engineering and Technology Research, Vol. 03, Issue. 46.
  6. Madhavi Kulkarni,Mayuri Lingayat, 2015,"Effective Product Ranking Method based on Opinion Mining", International Journal of Computer Applications (0975 – 8887),Volume 120 – No. 18.
  7. Arti Buche, Dr. M. B. Chandak, Akshay Zadgaonkar, 2013,"Opinion Mining And Analysis: A Survey", International Journal on Natural Language Computing (IJNLC), Vol. 2, No. 3.
  8. Aashutosh Bhatt, Ankit Patel, Harsh Chheda, Kiran Gawande, 2015, "Amazon Review Classification and Sentiment Analysis", International Journal of Computer Science and Information Technologies, Vol. 6.
  9. Asmita Dhokrat, Sunil Khillare, C. Namrata Mahender, 2015,"Review on Techniques and Tools used for Opinion Mining", International Journal of Computer Applications Technology and Research, Volume 4– Issue 6, 419 – 424.
  10. Farhan Hassan Khan, Saba Bashir and Usman Qamar, 2013,"TOM: Twitter opinion mining framework using hybrid classification scheme", Elsevier.
  11. Jayashri Khairnar and Mayura Kinikar , 2013,"Latent Semantic Analysis Method used for mobile rating and review summarization", International Journal of Computer Science and Telecommunications, Volume 4– Issue 6.
  12. Bing Liu, 2012, Sentiment analysis and opinion mining, Morgan & Claypool Publishers
  13. J. Ashok Kumar, S. Abirami, S. Murugappan, 2014, "Performance Analysis of the Recent Role of OMSA Approaches in Online Social networks", CS & IT-CSCP.
Index Terms

Computer Science
Information Sciences

Keywords

Opinion Sentiment Machine Learning Algorithm Reviews E-commerce