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
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Opinion Mining: A Survey

by K.g. Nandha Kumar, T Christopher
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 113 - Number 2
Year of Publication: 2015
Authors: K.g. Nandha Kumar, T Christopher
10.5120/19797-1576

K.g. Nandha Kumar, T Christopher . Opinion Mining: A Survey. International Journal of Computer Applications. 113, 2 ( March 2015), 15-17. DOI=10.5120/19797-1576

@article{ 10.5120/19797-1576,
author = { K.g. Nandha Kumar, T Christopher },
title = { Opinion Mining: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 113 },
number = { 2 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 15-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume113/number2/19797-1576/ },
doi = { 10.5120/19797-1576 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:49:54.382105+05:30
%A K.g. Nandha Kumar
%A T Christopher
%T Opinion Mining: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 113
%N 2
%P 15-17
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Opining mining has gained high level focus in business and commercial fields. The opinions are considered as valuable data. Opinions are customer reviews, comments and feelings and collected from web forums, websites, and user groups which are posted by thousands of end users and also recorded manually. The collected opinions are processed by various techniques, algorithms, methods and software tools in order to extract the meaning from them. Extraction of meaningful information from opinions is given more importance in the field of business analytics. This entire process is popularly known as opinion mining or sentiment analysis and they are used in industries to develop quality of services, products. This article is an outcome of a study which made on various sub tasks, approaches, methods and techniques involved and applied in opinion mining.

References
  1. Alaa El-Halees. 2011, Arabic Opinion Mining Using Combined Classification Approach, International Arab Conference On Information Technology (ACIT), Riyadh, Saudi Arabia.
  2. Aldo Gangemi, Valentina Presutti et al. 2014, Frame-Based Detection of Opinion Holders and Topics: A Model and A Tool, IEEE Computational Intelligence Magazine, 20 - 30.
  3. Anais Cadilhac, Farah Benamara et al. 2010, Ontolexical Resources for Feature Based Opinion Mining: A Case Study, Proceedings of the 6th Workshop on Ontologies and Lexical Resources (Ontolex 2010), Beijing, 77 - 86.
  4. Chihli Hung and Hao-Kai Lin. 2013, Using Objective Words in Sentiwordnet To Improve Word-Of-Mouth Sentiment Classification, IEEE Intelligent Systems, 47 - 54.
  5. Chi-Hwan Choi, Jeong-Eun Lee et al. 2013, Sentiment Analysis For Customer Review Sites, Proceedings of The 3rdInternational Conference On Circuits, Control, Communication, Electricity, Electronics, Energy, System, Signal And Simulation, CES-CUBE- ASTL Vol. 25, 157 - 162.
  6. Erik Cambria, Bjorn Schuller et al. 2013, New Avenues in Opinion Mining and Sentiment Analysis, IEEE Intelligent Systems, 15 - 21.
  7. Hsinchum Chen and David Zimbra 2010, AI and Opinion Mining, IEEE Intelligent Systems, 74 - 80.
  8. Lisette Garcia-Moya, Henry Anaya-Sanchez et al. 2013, Retrieving Product Features and Opinions from Customer Reviews, IEEE Intelligent Systems, 19 - 27.
  9. Marie-Catherine de Marneffe, Bill MacCartney et al. 2006, Generating typed dependency parses from phrase structure parses, Proceedings of international conference on language resources and evaluation, Vol. 6, 449 - 454.
  10. Michel Plantie, Mathieu Roche et al. 2008, Is A Voting Approach Accurate For Opinion Mining? Proceeding DaWaK '08 - Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery, 413 – 422.
  11. Poongodi S and Radha N. 2013, Classification Of User Opinions From Tweets Using Machine Learning Techniques, International Journal Of Advanced Research In Computer Science And Software Engineering, 1061 - 1065.
  12. Sachin A. Kadam and Shweta T. Joglekar (2013), Sentiment Analysis: An Over View, International Journal of Research in Engineering & Advanced Technology, Vol. 1, Issue 4, pp. 1 - 7.
  13. Tamilselvi A and Parveentaj M (2013), Sentiment Analysis Of Micro Blogs Using Opinion Mining Classification Algorithm, International Journal Of Science And Research, Vol. 2, Issue 10, pp. 196 - 202.
  14. Xiuzhen Zhang, Zhixin Zhou et al. 2009, Positive, Negative, or Mixed? Mining Blogs for Opinions, Proceedings of the 14th Australian Document Computing Symposium, Sydney.
  15. Zhongwu Zhai, Bing Liu et al. 2012, Product Feature Grouping For Opinion Mining, IEEE Intelligent Systems, 37- 44.
  16. Zhu Zhang. 2008, Weighing Stars: Aggregating Online Product Reviews For Intelligent E-Commerce Applications", IEEE Intelligent Systems, 42- 49.
Index Terms

Computer Science
Information Sciences

Keywords

Opinion Sentiment Classification Machine Learning NLP.

Powered by PhDFocusTM