Support Vector Machine and Naïve Bayes comparison of Sentiments on Terrorism

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Muhammad Umer Haroon
10.5120/ijca2018916022

Muhammad Umer Haroon. Support Vector Machine and Naïve Bayes comparison of Sentiments on Terrorism. International Journal of Computer Applications 179(17):15-17, February 2018. BibTeX

@article{10.5120/ijca2018916022,
	author = {Muhammad Umer Haroon},
	title = {Support Vector Machine and Naïve Bayes comparison of Sentiments on Terrorism},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2018},
	volume = {179},
	number = {17},
	month = {Feb},
	year = {2018},
	issn = {0975-8887},
	pages = {15-17},
	numpages = {3},
	url = {http://www.ijcaonline.org/archives/volume179/number17/28958-2018916022},
	doi = {10.5120/ijca2018916022},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Text Analysis has become a major area of research. In order to be aware of what people think and how they feel after terrorism attacks, there needs to be some mechanism. We aim to propose a solution in this regard to learn about people's sentiments in detail on terrorism incidents in Pakistan using text analysis. In this research support vector machines and naïve Bayes algorithms are compared in finding out the sentiments from data set of opinions express on terrorism activities in Pakistan.

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Keywords

Sentiments, Text analysis, terrorism incidents.