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A Survey on Sentiment Analysis Algorithms for Opinion Mining

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 133 - Number 9
Year of Publication: 2016
Authors:
Vidisha M. Pradhan, Jay Vala, Prem Balani
10.5120/ijca2016907977

Vidisha M Pradhan, Jay Vala and Prem Balani. Article: A Survey on Sentiment Analysis Algorithms for Opinion Mining. International Journal of Computer Applications 133(9):7-11, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Vidisha M. Pradhan and Jay Vala and Prem Balani},
	title = {Article: A Survey on Sentiment Analysis Algorithms for Opinion Mining},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {9},
	pages = {7-11},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Opinion mining and sentiment analysis is rapidly growing area. There are numerous e-commerce sites available on internet which provides options to users to give feedback about specific product. These feedbacks are very much helpful to both the individuals, who are willing to buy that product and the organizations. An accurate method for predicting sentiments could enable us, to extract opinions from the internet and predict customer’s preferences. There are various algorithms available for opinion mining. Before applying any algorithm for polarity detection, pre-processing on feedback is carried out. From these pre-processed reviews opinion words and object on which opinion is generated are extracted and any opinion mining technique is applied to find the polarity of the review. Opinion mining has three levels of granularities: Document level, Sentence level and Aspect level. In this paper various algorithms for sentiment analysis are studied and challenges and applications appear in this field are discussed.

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Keywords

Sentiment Analysis, Opinion Mining, Web Content, Machine Learning.