Using big data to understand the online ecology of COVID-19 vaccination hesitancy

Shasha Teng, Nan Jiang, Kok Wei Khong

Research output: Journal PublicationArticlepeer-review

9 Citations (Scopus)


With a large population of people vaccinated, it is possible that at-risk people are shielded, and the coronavirus disease is contained. Given the low vaccine uptakes, achieving herd immunity via vaccination campaigns can be challenging. After a literature review, we found a paucity of research studies of vaccine hesitancy from social media settings. This study aims to categorise and create a typology of social media contents and assess the priority of concerns for future public health messaging. With a dataset of 43,203 YouTube comments, we applied text analytics and multiple regression analyses to examine the correlations between vaccine hesitancy factors and vaccination intention. Our major findings are (i) Polarized views on vaccines existed in the social media ecology of public discourse, with a majority of people unwilling to get vaccinated against COVID-19; (ii) Reasons behind vaccine hesitancy included concerns about vaccine safety, potential side-effects, lack of trust in government and pharmaceutical companies; (iii) Political partisan-preferences were exemplified in vaccine decision-making processes; (iv) Anti-vaccine movements with amplified misinformation fuelled vaccine hesitancy and undermined public confidence in COVID-19 vaccines. We suggest public health practitioners engage in social media and craft evidenced-based messages to online communities in a balanced and palatable way.

Original languageEnglish
Article number158
Number of pages15
JournalHumanities and Social Sciences Communications
Issue number1
Publication statusPublished - 6 May 2022
Externally publishedYes

ASJC Scopus subject areas

  • General Business,Management and Accounting
  • General Arts and Humanities
  • General Social Sciences
  • General Psychology
  • Economics, Econometrics and Finance (all)


Dive into the research topics of 'Using big data to understand the online ecology of COVID-19 vaccination hesitancy'. Together they form a unique fingerprint.

Cite this