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Reseach Article

Opinion Mining: Issues and Challenges (A survey)

by Bakhtawar Seerat, Farouque Azam and
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 9
Year of Publication: 2012
Authors: Bakhtawar Seerat, Farouque Azam and
10.5120/7658-0762

Bakhtawar Seerat, Farouque Azam and . Opinion Mining: Issues and Challenges (A survey). International Journal of Computer Applications. 49, 9 ( July 2012), 42-51. DOI=10.5120/7658-0762

@article{ 10.5120/7658-0762,
author = { Bakhtawar Seerat, Farouque Azam and },
title = { Opinion Mining: Issues and Challenges (A survey) },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 9 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 42-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number9/7658-0762/ },
doi = { 10.5120/7658-0762 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:45:52.426922+05:30
%A Bakhtawar Seerat
%A Farouque Azam and
%T Opinion Mining: Issues and Challenges (A survey)
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 9
%P 42-51
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Opinion mining is crucial for both individuals and companies. Individuals may want to see the opinion of other customers about a product to analyze it before buying it. Companies want to analyze the feedback of customers about their products to make future decisions. So, analyzing customer's opinion and their response is important. Mining is used on product reviews that are available on different blogs, web forums, and product review sites to evaluate opinions of customers. By doing so, new customers are able to find views of others about a product and can decide which product to buy by the help of opinion of customers already using the product. In addition comparison of same feature of products by different vendors is done. In this way companies can focus on improving the features of their product that are not popular among customers. This leads to overcome the requirements of marketing intelligence and product benchmarking in the production industry. In this paper we do a survey of papers and will summarize the issues and challenges of opinion mining that affect the results of opinion mining.

References
  1. Z. M. Ma. 2005. Databases Modeling of Engineering Information, Northeastern University, China
  2. M. Mehdi Owrang O. 2007. Discovering Quality Knowledge from Relational Databases, American University, USA.
  3. Bing Liu. 2011. Sentiment Analysis Tutorial - Given at AAAI-2011, San Francisco, USA.
  4. Bing Liu. 2007. Opinion Mining, Department of Computer Science University of Illinois at Chicago.
  5. Andreas Auinger, Martin Fischer. 2008. Mining consumers' opinions on the web.
  6. Qingyu Zhang and Richard S. Segall . 2008. Web Mining: a Survey of Current Research, Techniques, and Software.
  7. Lita van Wel and Lamber Royakkers. 2004. Ethical issues in web data mining, Department of Philosophy and Ethics of Technolog.
  8. Liu, B. , Hu, M. and Cheng, J. 2005. Opinion Observer. Analyzing and Comparing Opinions on the Web. Proceedings of International World Wide Web Conference (WWW'05).
  9. Ganesan, K. A. , and H. D. Kim. 2008. Opinion Mining - A Short Tutorial (Talk) , University of Illinois at Urbana Champaign.
  10. Ganapathibhotla, G. and Liu, B. 2008. Identifying Preferred Entities in Comparative Sentences. To appear in Proceedings of the 22nd International Conference on Computational Linguistics (COLING'08).
  11. Jindal, N. and Liu, B. Mining. 2006. Comparative Sentences and Relations. Proceedings of National Conference on Artificial Intelligence (AAAI'06).
  12. Ana Azevedo AND M F Santos. 2008. Kdd, Semma and Crisp-Dm. A Parallel Overview
  13. H D U K Kim, K. Ganesan, P Sondhi, C Zhai. 2011. Comprehensive Review of Opinion Summarization.
  14. Alexandra Balahur and Andrés Montoy. 2010. OpAL. Applying Opinion Mining Techniques for the Disambiguation of Sentiment Ambiguous Adjectives in SemEval-2 Task 18.
  15. Anna Stavrianou and Jean-Hugues Chauchat. 2008. Opinion Mining Issues and Agreement Identification in Forum Texts.
  16. Andrea Esuli. 2008. Automatic Generation of Lexical Resources for Opinion Mining. Models, Algorithms and Applications.
  17. Krisztian Balog, Maarten de Rijke. 2006. Decomposing Bloggers' Moods - Towards a Time Series Analysis of Moods in the Blogosphere
  18. Marina Sokolova, Guy Lapalme. 2008. Verbs Speak Loud. Verb Categories in Learning Polarity and Strength of Opinions.
  19. Animesh Kar, Deba Prasad Mandal. 2011. Finding Opinion Strength Using Fuzzy Logic on Web Reviews.
  20. B. Ohana, B. Tierney. 2011. Opinion Mining with SentiWordNet.
  21. Zhongwu Zhai, Bing Liu. 2011. Identifying Evaluative Sentences in Online Discussions.
  22. Hyun Duk Kim, ChengXiang Zhai. 2009. Generating comparative summaries of contradictory opinions in text.
  23. Murthy Ganapathibhotla, Bing Liu. 2008. Mining opinions in comparative sentences.
  24. Bo Pang and Lillian Lee. 2008. Opinion Mining and Sentiment Analysis, Department of Computer Science University of Illinois at Chicago.
  25. Christopher C. Yang, Y. C. Wong. 2008. Mining consumer opinions from the Web.
  26. South Morgan Street, Bing Liu. 2011. Identifying Noun Product Features that Imply Opinions.
  27. Bing Liu. 2010. Sentiment Analysis: A Multi-Faceted Problem.
Index Terms

Computer Science
Information Sciences

Keywords

Knowledge discovery Data Mining Web Mining Opinion Mining Sentiment Analysis Issues Challenges