Garg, Harshit, Jhunthra, Srishti, Goel, Rahul, Sharma, Shakshi, Gupta, Vedika, Sharma, Rajesh and Dass, Pranav (2024) Understanding user polarisation regarding COVID-19 vaccines through social network analysis. Journal of Discrete Mathematical Sciences and Cryptography, 27 (8). pp. 2301-2336. ISSN 0972-0529
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Abstract
Whenever any critical incident comes into the limelight, people tend to discuss it over social media platforms to exchange ideas, perspectives and opinions globally. Sometimes the chain of discussions lead to generation of new perspectives and enhance the general understanding of short-term or long-term implications of the problem at hand. Social media platforms have been an important tool to study and analyse opinions of stakeholders, consumers, citizens, customers, or clients. If positive, these opinions can help gain confidence for a business product or policy law. If otherwise the negative opinions can help the business, or the government understand online social media users about their feelings and take the necessary steps to counter bad reputation and promote customer satisfaction. Having an in-depth descriptive understanding of how the state of things are, leads to a realization of what circumstantial strategies should be adopted or followed to tackle such scenarios. This paper presents the as-is scenario of discussions held on social media platform Twitter regarding the various vaccines for COVID-19, which has been a critical topic of interest worldwide.
This study proposes a detailed analysis of the variety of perspectives and user polarisation persisting on Twitter in different dimensions. We segment Twitter users into two categories proponents (those propelling the idea of vaccination) and opponents (those opposing the idea of vaccination). Further, we have also categorized the Twitterati (Twitter users) on the basis of information seekers (inquisitive), information providers (informative) and opinion providers (opinionated). The analysis shows us the change of thoughts and opinions of the twitter users over a period of time. Overall, the paper presents quantitative and qualitative analysis depicting some analytical views taking different parameters into consideration.
Item Type: | Article |
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Keywords: | Twitter | COVID-19 | Vaccinations | Natural language processing | Networks | Social media |
Subjects: | Social Sciences and humanities > Decision Sciences > Information Systems and Management Social Sciences and humanities > Social Sciences > Social Sciences (General) Social Sciences and humanities > Social Sciences > Health (Social sciences) |
JGU School/Centre: | Jindal Global Business School |
Depositing User: | Dharmveer Modi |
Date Deposited: | 15 Jan 2025 09:48 |
Last Modified: | 15 Jan 2025 09:48 |
Official URL: | https://doi.org/10.47974/JDMSC-1859 |
URI: | https://pure.jgu.edu.in/id/eprint/9014 |
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