CFP last date
20 December 2024
Reseach Article

A Review On: Opinion Mining and Sentiment Analysis based on Natural Language Processing

by Swati N. Manke, Nitin Shivale
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 109 - Number 4
Year of Publication: 2015
Authors: Swati N. Manke, Nitin Shivale
10.5120/19179-0653

Swati N. Manke, Nitin Shivale . A Review On: Opinion Mining and Sentiment Analysis based on Natural Language Processing. International Journal of Computer Applications. 109, 4 ( January 2015), 29-32. DOI=10.5120/19179-0653

@article{ 10.5120/19179-0653,
author = { Swati N. Manke, Nitin Shivale },
title = { A Review On: Opinion Mining and Sentiment Analysis based on Natural Language Processing },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 109 },
number = { 4 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume109/number4/19179-0653/ },
doi = { 10.5120/19179-0653 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:43:54.908525+05:30
%A Swati N. Manke
%A Nitin Shivale
%T A Review On: Opinion Mining and Sentiment Analysis based on Natural Language Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 109
%N 4
%P 29-32
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In marketing and advertising domains Opinion Mining is being larger domain. Advertiser needs to analyze performance/ popularity of ads that he/she posted on site. Star rating based mechanism may go fraud, because of robots or automatic responders. So, current system needs to be analyzed using comments & natural language processing. Fraud comments could be removed by using irrelevant comment removal mechanism suggested in paper. In this paper the role and importance of social networks as preferred environments for opinion mining and sentiment analysis are discussed especially. In this paper, selected properties of social networks that are relevant with respect to opinion mining are briefly described and outline the general relationships between the two disciplines. It presents the related work and provide basic definitions used in opinion mining area. Then, the original method of opinion classification is introduce and test the presented algorithm on real world datasets acquired from popular Polish social networks, reporting on the results. The results are outperform and soundly support the main issue of the paper, that social networks exhibit properties that make them very suitable for opinion mining activities.

References
  1. Zhen Hai, Kuivyu , Jung-Jae Kim, and Christopher C. Yang "Identify Features in opinion mining via intrinsic and extrinsic Domain Relevance" Vol 26, no. 3, March 2014.
  2. W. Jin and H. H. Ho, "A Novel Lexicalized HMM-Based Learning Framework for Web Opinion Mining," Proc. 26th Ann. Int'l Conf. Machine Learning, pp. 465-472, 2009.
  3. N. Jakob and I. Gurevych, "Extracting Opinion Targets in a Single and Cross-Domain Setting with Conditional Random Fields," Proc. Conf. Empirical Methods in Natural Language Processing, pp. 1035-1045, 2010.
  4. G. Qiu, B. Liu, J. Bu, and C. Chen, "Opinion Word Expansion and Target Extraction through Double Propagation," Computational Linguistics, vol. 37, pp. 9-27, 2011. .
  5. Sannella, M. J. . M. Kim and E. Hovy, "Extracting Opinions Holders, and Topics Expressed in Online News Media Text," Proc. ACL/COLING Workshop Sentiment and Subjectivity in Text, 2006.
  6. Forman, B. Pang and L. Lee, "A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts," Proc. 42nd Ann. Meeting on Assoc. for Computational Linguistics.
  7. Brown, L. D. , Hua, M. Hu and B. Liu, "Mining and Summarizing Customer Reviews," Proc. 10th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, pp. 168-177, 2004.
  8. B. Liu, "Sentiment Analysis and Opinion Mining," Synthesis Lectures on Human Language Technologies, vol. 5, no. 1, pp. 1-167,May 2012 .
  9. Y. Jo and A. H. Oh, "Aspect and Sentiment Unification Model for Online Review Analysis," Proc. Fourth ACM Int'l Conf. Web Search and Data Mining, pp. 815-824, 2011.
  10. G. Qiu, C. Wang, J. Bu, K. Liu, and C. Chen, "Incorporate the Syntactic Knowledge in Opinion Mining in User-Generated Content," Proc. WWW 2008 Workshop NLP Challenges in the Information Explosion Era, 2008.
  11. A. Popescu and O. Etzioni, "Extracting Product Features and Opinions from Reviews," Proc. Human Language Technology Conf. and Conf. Empirical Methods in Natural Language Processing, pp. 339- 346, 2005.
  12. V. Hatzivassiloglou and J. M. Wiebe, "Effects of Adjective Orientation and Gradability on Sentence Subjectivity," Proc. 18th Conf. Computational Linguistics, pp. 299-305, 2000.
  13. Q. Su, X. Xu, H. Guo, Z. Guo, X. Wu, X. Zhang, B. Swen, and Z. Su,"Hidden Sentiment Association in Chinese Web Opinion Mining,"Proc. 17th Int'l Conf. World Wide Web, pp. 959-968, 2008
Index Terms

Computer Science
Information Sciences

Keywords

Opinion Sentiment Domain-dependent corpus Domain-independent corpus Relevance.