Analyzing the Sentiments by Classifying the Tweets Based on COVID-19 Using Machine Learning Classifiers


In the current scenario, almost all the countries face one of the biggest disasters in COVID-19. This paper has to analyze the tweets related to COVID 19 and discuss the various machine learning algorithms and their performance analysis on the tweets associated with COVID-19. The implemented classification algorithms are applied to classify the sentiments to predict whether they relate to COVID-19 or non-COVID-19. Ten most popular classification algorithms implemented. The Linear Support Vector Machine (LSVM) achieved the highest test accuracy in these algorithms with 90.3%. Logistic regression has performed better in recall with 96.06%, F1 score of 90.46%, ROC_AUC with 90.48%. Random forest classifier has achieved the better specificity and precision of 99.16% and 96.3%, respectively. Out of all, stochastic gradient descent (SGD) has attained better results in all the computational parameters

In 2021 IEEE International Conference on Technology, Research, and Innovation for Betterment of Society (TRIBES)