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Reseach Article

Sentiment Analysis of Political Reviews in Punjabi Language

by Parul Arora, Brahmaleen Kaur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 14
Year of Publication: 2015
Authors: Parul Arora, Brahmaleen Kaur
10.5120/ijca2015906297

Parul Arora, Brahmaleen Kaur . Sentiment Analysis of Political Reviews in Punjabi Language. International Journal of Computer Applications. 126, 14 ( September 2015), 20-23. DOI=10.5120/ijca2015906297

@article{ 10.5120/ijca2015906297,
author = { Parul Arora, Brahmaleen Kaur },
title = { Sentiment Analysis of Political Reviews in Punjabi Language },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 14 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 20-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number14/22621-2015906297/ },
doi = { 10.5120/ijca2015906297 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:17:59.042731+05:30
%A Parul Arora
%A Brahmaleen Kaur
%T Sentiment Analysis of Political Reviews in Punjabi Language
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 14
%P 20-23
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sentiment Analysis is to distinguish and group the assessments/feelings/opinions in composed content. Till date, English Language incorporates the majority of the examination work around there. In this paper, we talked about the different methodologies used to finish the opinion investigation and exploration work accomplished for Indian Languages like Hindi, Bengali and Telugu. An approach is proposed to determine the sentiment orientation i.e. polarity of the Punjabi reviews by scoring method. Sentiment analysis is needed to be performed in Punjabi language because of the increase in Punjabi data on the web. Separate positive and negative condensed results are created which is useful for the client in choice making. We contrasted the outcomes and right now existing methodologies.

References
  1. Deepak Ravichandran,” Semi-Supervised Polarity Lexicon Induction”, Proceedings of the Third IEEE International Conference on Data Mining, 2009.
  2. V.K. Singh, R. Piryani,” Sentiment Analysis of Movie Reviews A new Feature-based Heuristic for Aspect-level Sentiment Classification”, IEEE, 2013.
  3. Er.Parul Arora, Er.Brahmaleen Kaur, ”An approach for Sentiment Analysis for Punjabi Text. International Journal of Information Technology& Computer Sciences Perspectives© Pezzottaite Journals. 1452|Page, Volume 4, Number 2, April – June‟ 2015 ISSN (Print):2319-9016, (Online):2319-9024 PEZZOTTAITE JOURNALS SJIF (2012): 3.201, SJIF (2013): 5.058, SJIF (2014): 5.891
  4. K. Dave, S. Lawerence & D. Pennock, “Mining the Peanut Gallery-Opinion Extraction and Semantic Classification of Product Reviews”, Proceedings of the 12th International World Wide Web Conference, pp. 519-528, 2003.
  5. P. Turney, “Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews”, Proceedings of ACL-02, 40th Annual Meeting of the Association for Computational Linguistics, pp. 417-424, Philadelphia, US, 2002.
  6. A. Esuli & F.Sebastiani, “Determining the Semantic Orientation of terms through gloss analysis”, Proceedings of CIKM-05, 14th ACM International Conference on Information and Knowledge Management, pp. 617-624, Bremen, DE, 2005.
  7. Christos Troussas,” Predicting Movie Sales Revenue using Online Reviews”IJRRC,2012.
  8. Troussas,“Sentiment analysis of Face book statuses using Naive Bayes classifier for language learning”,ACM International Conference on Information and Knowledge Management, 2013.
  9. Ms.K.Mouthami, Arzu Baloglu "Sentiment Analysis and Classification Based On Textual Reviews",Fifth International Conference on Internet and Web Applications and Services, 2010
  10. Neethu M S, Christos TroussasA. Agarwal, B. Xie, I. Vovsha, O. Rambow, R. Passonneau, "Sentiment Analysis in Twitter using Machine Learning Techniques",Sentiment analysis of Twitter data”, LSM '11 Proceedings of the Workshop on Languages in Social Media, Association for Computational Linguistics, pp. 30-38, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Sentiment Analysis Punjabi Language Senti Word Net