Sentiment Analysis on Twitter's Big Data Against the Covid-19 Pandemic Using Machine Learning Algorithms - Part 25

Aug 3, 2026

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This paper analyzes users’ reactions on Twitter to the COVID-19 pandemic by applying machine learning and data mining to classify tweets according to economic and health fears. A large dataset of tweets is explored through extraction, transformation, loading, cleansing, and analysis. A proposed framework enhances prediction quality using a dictionary for tweet classification. Four supervised algorithms are compared, and Naive Bayes delivers the highest percentage of correct predictions.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages11

Reading Time28 min

AccessFree to download

Introduction

Background on Big Data, Machine Learning, and Data Mining

Sentiment Analysis on Tweets

Contributions of the Paper

Information Sciences Letters | Volume 12
Issue 8 Aug. 2023 | Article 25 | | --- | --- | | 2023
Sentiment Analysis on Twitters Big Data Against the Covid-19 Pandemic Using Machine Learning Algorithms
Awny Sayed
Computer Science Department, Faculty of Science, Minia University, Minia 61519, Egypt, [mostafa.nazier@gmail.com](mostafa.nazier@gmail.com)
Mamdouh M. Gomaa
Computer Science Department, Faculty of Science, Minia University, Minia 61519, Egypt, [mostafa.nazier@gmail.com](mostafa.nazier@gmail.com)
Mostafa Medhat Nazier
Computer Science Department, Faculty of Science, Minia University, Minia 61519, Egypt, [mostafa.nazier@gmail.com](mostafa.nazier@gmail.com)
Follow this and additional works at: [https://digitalcommons.aaru.edu.jo/isl](https://digitalcommons.aaru.edu.jo/isl) | | 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](https://digitalcommons.aaru.edu.jo/isl/vol12/iss8/25) This Article is brought to you for free and open access by Arab Journals Platform. It has been accepted for inclusion in Information Sciences Letters by an authorized editor. The journal is hosted on Digital Commons, an Elsevier platform. For more information, please contact [rakan@aaru.edu.jo](rakan@aaru.edu.jo), [marah@aaru.edu.jo](marah@aaru.edu.jo), [u.murad@aaru.edu.jo](u.murad@aaru.edu.jo). Information Sciences Letters An International Journal [http://dx.doi.org/10.18576/isl/120825](http://dx.doi.org/10.18576/isl/120825) Sentiment Analysis on Twitter's Big Data Against the Covid- 19 Pandemic Using Machine Learning Algorithms Awny Sayed, MamdouhM. Gomaa and Mostafa Medhat Nazier * Computer Science Department, Faculty of Science, Minia University, Minia 61519, Egypt Received: 27 May 2023, Revised: 13 Jul. 2023, Accepted: 23 Jul. 2023. Published online: 1 Aug. 2023 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 algorithmsand finds that people discuss the pandemic's dangers from economic and health perspectives with equal frequency. The Naive Bayes algorithm achieves the highest percentage of correct predictions. Keywords: Machine Learning (ML); Big Data (BD); Data Mining (DM); Sentiment Analysis (SA); Naive Bayes (NB); Supported Vector Machine (SVM); Decision Trees (DT); Generalized Linear Model (GLM) . 1 Introduction Corona's disease has now become an epidemic, with a rapid and widespread spread in most countries around the world, and the size of the big data issued by social media platforms necessitates analysis of this data for scientific forecasting of what will happen in the short and long term, as well as people's perceptions of this pandemic and how people will spend this isolation time with their families. The use of Big Data, Machine Learning, and Data Mining algorithms and techniques in analyzing Big Data exported from a social networking platform like Twitter to analyze the tweets of people around the world about this pandemic represents a treasure that will be useful in studying the impact of this pandemic on people, both economically and socially. Big Data refers to a variety of different formats of data that are produced from different sources [1] . It is a massive amount of unstructured and structured data [2] . Big data technology contributes to development, governance, search, integration, and analytics s

FAQs

What problem does the paper address using Twitter data?

The paper studies users’ reactions to the COVID-19 pandemic on Twitter, focusing on economic and health fears reflected in tweets.

How does the proposed framework improve tweet classification?

It improves prediction quality by using a proposed dictionary within a machine learning based classification framework.

Which supervised machine learning algorithm performs best?

The Naive Bayes algorithm achieves the highest percentage of correct predictions among the four compared supervised models.

Aug 3, 2026

Upload by Patrick