Sentiment Analysis on Twitters Big Data Against the Covid- 19 Pandemic Using Machine Learning Algorithms

Authors

Awny Sayed, Computer Science Department, Faculty of Science, Minia University, Minia 61519, EgyptFollow
Mamdouh M. Gomaa, Computer Science Department, Faculty of Science, Minia University, Minia 61519, EgyptFollow
Mostafa Medhat Nazier, Computer Science Department, Faculty of Science, Minia University, Minia 61519, EgyptFollow

Abstract

This paper analyzes users reactions on Twitter to the COVID-19 pandemic, using machine learning and data mining algorithms to classify tweets according to economic and health fears. A large dataset of tweets is explored, extracted, transformed, loaded, cleansed, and analyzed. The proposed framework improves prediction quality with a proposed dictionary that is used to classify tweets. The study compares four supervised machine learning algorithms and finds that people discuss the pandemics dangers from economic and health perspectives with equal frequency. The Naive Bayes algorithm achieves the highest percentage of correct predictions.

Recommended Citation

Sayed, Awny; M. Gomaa, Mamdouh; and Medhat Nazier, Mostafa (2023) "Sentiment Analysis on Twitters Big Data Against the Covid- 19 Pandemic Using Machine Learning Algorithms," Information Sciences Letters: Vol. 12 : Iss. 8 , PP -.
Available at: https://digitalcommons.aaru.edu.jo/isl/vol12/iss8/25