Improved Opinion Mining System to Enhance Accuracy using SVM with RBF Kernel
Umakant Sharma
Dept. of Software Engineering , IN
Abhilash Mishra
Dept. of Software Engineering , IN
Keywords: opinion mining; model; application; SVM; RBF kernel.
Abstract
Opinions in social media platforms provide worldwide access to what people think about daily life topics/issues. Thus exploiting such a source of data to comprehend popular opinion can be exceptionally valuable in numerous situations, for instance by political gatherings keen on observing attitudes towards their policies. The opinion mining research field aims to develop automated approaches to accurately analyze such opinion data. Although there is much previous work on opinion mining, the majority of early studies analyzed text documents such as product and movie reviews. Only a limited number of studies have attempted to analyze public opinion in a political context. Twitter, which is now and again called a buy in and- publish social network, gives coordinated connections among users' and hosts feeling rich data over a wide arrangement of users' and points. In this manner, it is clear that mining client opinions and estimations from Twitter will be exceptionally valuable for some applications.
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