Social network analysis of COVID-19 vaccine YouTube videos in Odisha, India: mapping the channel network and analyzing comment sentiment

Author:

Alperstein NeilORCID,Pascual-Ferrá Paola,Ganjoo Rohini,Bhaktaram Ananya,Burleson Julia,Barnett Daniel J.,Jamison Amelia M.,Kluegel Eleanor,Mohanty Satyanarayan,Orton Peter Z.,Parida Manoj,Rath Sidharth,Rimal Rajiv

Abstract

AbstractIndia has reported more than 35 million confirmed cases of COVID-19 and nearly half a million cumulative deaths. Although vaccination rates for the first vaccine dose are quite high, one-third of the population has not received a second shot. Due to its widespread use and popularity, social media can play a vital role in enhancing vaccine acceptance. This study in a real-world setting utilizes YouTube videos in Odisha, India where the platform has deep penetration among the 18–35 target population, and secondarily their family and peers. Two contrasting videos were launched on the YouTube platform to examine how those videos operate within the broader recommender and subscription systems that determine the audience reach. Video analytics, algorithms for recommended videos, visual representation of connections created, centrality between the networks, and comment analysis was conducted. The results indicate that the video with a non-humorous tone and collectivistic appeal delivered by a female protagonist performed best with regard to views and time spent watching the videos. The results are of significance to health communicators who seek to better understand the platform mechanisms that determine the spread of videos and measures of viewer reactions based on viewer sentiment.

Funder

Vaccine Confidence Fund

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine

Reference28 articles.

1. Center for Systems Science and Engineering (CSSE). (2022). COVID-19 Dashboard. Johns Hopkins University. Retrieved from https://coronavirus.jhu.edu/map.html. Accessed 15 Mar 2022.

2. Chowdhury, S., Motheram, A., Pramanik, S. Covid-19 vaccine hesitancy: Trends across states, over time. Ideas for India. 2021. Retrieved from https://www.ideasforindia.in/topics/governance/covid-19-vaccine-hesitancy-trends-across-states-over-time.html. Accessed 15 Mar 2022.

3. Menon, S. Covid-19: How India missed its vaccination target. BBC News. 2021. Retrieved from https://www.bbc.com/news/world-asia-india-55571793. Accessed 15 Mar 2022.

4. Reuters. India says gap between vaccine doses based on scientific evidence. Reuters. 2021. Retrieved from https://www.reuters.com/world/india/opposition-questions-india-govt-doubling-vaccine-dosing-gap-2021-06-16/. Accessed 15 Mar 2022.

5. Indian Council of Medical Research. India COVID-19 Vaccine Tracker. Ministry of Health and Family Welfare. 2021. Retrieved from https://analytics.icmr.org.in/public/dashboard/149a9c89-de6d-4779-9326-5e8fed3323b6. Accessed 15 Mar 2022.

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