COVID-19 Vaccination Opinions in Education-Related Tweets

Erik-Robert Kovacs (), Liviu-Adrian Cotfas () and Camelia Delcea ()
Additional contact information
Erik-Robert Kovacs: Bucharest University of Economic Studies
Liviu-Adrian Cotfas: Bucharest University of Economic Studies
Camelia Delcea: Bucharest University of Economic Studies

A chapter in Eurasian Business and Economics Perspectives, 2022, pp 21-41 from Springer

Abstract: Abstract The coronavirus pandemic has forced authorities to take unprecedented measures, including the temporary closure of business and the instauration of national and regional lockdowns. The educational system, one of the key components of the society, has also been disrupted, as many schools and universities have moved their courses online for prolonged periods. With the introduction of the first vaccine on December 8, 2020, social media users have reacted by posting messages supporting or rejecting the vaccination process. In this context, the present paper aims to analyze the opinions regarding COVID-19 vaccination in education-related tweets. A dataset containing 102,805 English tweets published in the month following the beginning of the vaccination process has been collected. Several classical machine learning and deep learning algorithms have been compared and the best-performing classifier, RoBERTa, has been selected and applied for determining the stance of the collected tweets, as in favor, against or neutral. The evolution of the opinions has been put in correspondence with the main events that have occurred during the analyzed period, while the main discussion topics have been outlined using the Latent Dirichlet Allocation and n-gram analysis. The obtained results can be useful for authorities looking to better understand the opinions of the parents, students, teachers, and general public.

Keywords: Social media analysis; Machine learning; Natural language processing; Stance analysis; Education (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:eurchp:978-3-031-15531-4_2

Ordering information: This item can be ordered from
http://www.springer.com/9783031155314

DOI: 10.1007/978-3-031-15531-4_2

Access Statistics for this chapter

More chapters in Eurasian Studies in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().