Twitter Sentiment Analysis of Mobile Reviews using kernelized SVM

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Driyani A, et. al.

Abstract

Sentiment analysis is a technique of analysing the opinions commented in social media on various topics. There are few ways the sentiment analysis can be done. Machine learning plays a crucial role for analysing the opinions and reviews. Mobile related tweets have been scraped from twitter. Noise on the tweets has been removed using pre-processing and feature vectors were created. Support Vector Machine has been used to classify the reviews as either positive or negative. 4 cross validation technique were used to bring out the better accuracy. 3 different sizes of dataset with iphone11 reviews have been used for training and testing with different kernels of SVM. RBF kernel is found to be working better for classifying the tweets but at the same time it has been found that the accuracy decreases when the data grow bigger.  

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How to Cite
et. al., D. A. (2021). Twitter Sentiment Analysis of Mobile Reviews using kernelized SVM. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(10), 765–768. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/4243
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