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

Abstract

India 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.