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Sentimental Analysis in Social Media using IGBA Algorithm

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
M. Yuvaraja, S. Thavamani
10.5120/ijca2018916860

M Yuvaraja and S Thavamani. Sentimental Analysis in Social Media using IGBA Algorithm. International Journal of Computer Applications 179(38):20-25, April 2018. BibTeX

@article{10.5120/ijca2018916860,
	author = {M. Yuvaraja and S. Thavamani},
	title = {Sentimental Analysis in Social Media using IGBA Algorithm},
	journal = {International Journal of Computer Applications},
	issue_date = {April 2018},
	volume = {179},
	number = {38},
	month = {Apr},
	year = {2018},
	issn = {0975-8887},
	pages = {20-25},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume179/number38/29325-2018916860},
	doi = {10.5120/ijca2018916860},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Social media observance has been growing day by day therefore analysing of social information plays a very important role in knowing user behaviour. This system has a tendency to square measure analysing Social knowledge like Twitter Tweets victimization sentiment analysis that checks the perspective of User post and review. This paper develops a new algorithm improved gradient boost algorithm is combined lexicon supported social media keywords and on-line review, post and conjointly realize hidden relationship pattern from these keyword. Finally proposed novel algorithm IGBA provide better performance compared with existing algorithm naïve Bayes classifier, Support vector machine classifier.

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Keywords

Data Mining, Sentiment Analysis, Social Network, Support Vector Machine, Naïve Bayes