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Support Vector Machine and Naïve Bayes comparison of Sentiments on Terrorism
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 179 - Number 17 |
| 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 ( Feb 2018), 15-17. DOI=10.5120/ijca2018916022
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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