The spread of COVID-19 vaccine information in Arabic on YouTube: A network exposure study

Nour Zeid, Lu Tang, Muhammad “Tuan” Amith

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: The Arabic-speaking world had the lowest vaccine rates worldwide. The region's increasing reliance on social media as a source of COVID-19 information coupled with the increasing popularity of YouTube in the Middle East and North Africa region begs the question of what COVID-19 vaccine content is available in Arabic on YouTube. Given the platform's reputation for being a hotbed for vaccine-related misinformation in English, this study explored the COVID-19 vaccine-related content an individual is likely to be exposed to on YouTube when using keyword-based search or redirected to YouTube from another platform from an anti-vaccine seed video in Arabic. Methods: Only using the Arabic language, four networks of videos based on YouTube's recommendations were created in April 2021. Two search networks were created based on Arabic pro-vaccine and anti-vaccine keywords, and two seed networks were created from conspiracy theory and anti-vaccine expert seed videos. The network exposure model was used to examine the video contents and network structures. Results: Results show that users had a low chance of being exposed to anti-vaccine content in Arabic compared to the results of a previous study of YouTube content in English. Of the four networks, only the anti-vaccine expert network had a significant likelihood of exposing the user to more anti-vaccine videos. Implications were discussed. Conclusion: YouTube deserves credit for its efforts to clean up and limit anti-vaccine content exposure in Arabic on its platform, but continuous evaluations of the algorithm functionality are warranted.

Original languageEnglish (US)
JournalDigital Health
Volume9
DOIs
StatePublished - Jan 1 2023

Keywords

  • Arabic
  • MENA
  • YouTube
  • network exposure analysis
  • vaccine acceptance
  • vaccine hesitancy

ASJC Scopus subject areas

  • Health Policy
  • Health Informatics
  • Computer Science Applications
  • Health Information Management

Fingerprint

Dive into the research topics of 'The spread of COVID-19 vaccine information in Arabic on YouTube: A network exposure study'. Together they form a unique fingerprint.

Cite this