Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data

Najwa Alshahrani; Ghidaa Alnefaiy; Sara Abduljaleel; Tahani Alqurashi; Zahyah H Alharbi

doi:10.5455/jeas.2023110108

JE&AS. 2023; 10(2): 109-118

doi: 10.5455/jeas.2023110108

Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data

Najwa Alshahrani, Ghidaa Alnefaiy, Sara Abduljaleel, Tahani Alqurashi, Zahyah H Alharbi.

Abstract
Social media has emerged as a critical communication tool in contemporary society, bringing the world closer by making news and opinions more accessible through virtual platforms. Among these, Twitter stands out with over 350 million users worldwide. However, the highly unstructured nature of Twitter data poses significant challenges for analysis. Recently, the rich content of social media networks has spurred extensive research, particularly in light of the COVID-19 pandemic that has impacted global populations. Concurrent with the search for a vaccine, numerous studies have focused on analyzing public sentiment during the crisis, using data from various social media platforms. This study concentrates on people's opinions regarding COVID-19 vaccines, employing several machine learning models to analyze data from Twitter. It was discovered that the most accurate algorithm was the SGD Classifier, which utilized all three n-gram ranges, achieving an accuracy of 0.75.

Key words: Arabic Tweets; COVID-19 Vaccines; Sentiment Analysis; Social Media;Twitter Data

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How to Cite this Article

Pubmed Style

Alshahrani N, Alnefaiy G, Abduljaleel S, Alqurashi T, Alharbi ZH. Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data. JE&AS. 2023; 10(2): 109-118. doi:10.5455/jeas.2023110108

Web Style

Alshahrani N, Alnefaiy G, Abduljaleel S, Alqurashi T, Alharbi ZH. Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data. https://jecasmu.org/?mno=180698 [Access: January 03, 2024]. doi:10.5455/jeas.2023110108

AMA (American Medical Association) Style

Alshahrani N, Alnefaiy G, Abduljaleel S, Alqurashi T, Alharbi ZH. Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data. JE&AS. 2023; 10(2): 109-118. doi:10.5455/jeas.2023110108

Vancouver/ICMJE Style

Alshahrani N, Alnefaiy G, Abduljaleel S, Alqurashi T, Alharbi ZH. Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data. JE&AS. (2023), [cited January 03, 2024]; 10(2): 109-118. doi:10.5455/jeas.2023110108

Harvard Style

Alshahrani, N., Alnefaiy, . G., Abduljaleel, . S., Alqurashi, . T. & Alharbi, . Z. H. (2023) Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data. JE&AS, 10 (2), 109-118. doi:10.5455/jeas.2023110108

Turabian Style

Alshahrani, Najwa, Ghidaa Alnefaiy, Sara Abduljaleel, Tahani Alqurashi, and Zahyah H Alharbi. 2023. Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data. Journal of Engineering and Applied Sciences-JE&AS, 10 (2), 109-118. doi:10.5455/jeas.2023110108

Chicago Style

Alshahrani, Najwa, Ghidaa Alnefaiy, Sara Abduljaleel, Tahani Alqurashi, and Zahyah H Alharbi. "Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data." Journal of Engineering and Applied Sciences-JE&AS 10 (2023), 109-118. doi:10.5455/jeas.2023110108

MLA (The Modern Language Association) Style

Alshahrani, Najwa, Ghidaa Alnefaiy, Sara Abduljaleel, Tahani Alqurashi, and Zahyah H Alharbi. "Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data." Journal of Engineering and Applied Sciences-JE&AS 10.2 (2023), 109-118. Print. doi:10.5455/jeas.2023110108

APA (American Psychological Association) Style

Alshahrani, N., Alnefaiy, . G., Abduljaleel, . S., Alqurashi, . T. & Alharbi, . Z. H. (2023) Sentiment Analysis on Arabic Public Opinions toward COVID-19 Vaccines Using Twitter Data. Journal of Engineering and Applied Sciences-JE&AS, 10 (2), 109-118. doi:10.5455/jeas.2023110108