Centers for Disease Control and Prevention. (2021, September 4). How to Address COVID-19 Vaccine Misinformation. https://www.cdc.gov/vaccines/covid-19/health-departments/addressing-vaccine-misinformation.html

University of California, Berkeley

AI Agents

Misinformation/disinformation about vaccines that can affect vaccine confidence and vaccination rates.

Vaccine Misinformation

 • The rise of social media use and outreach has raised the influence of vaccine misinformation more than any time in history.

 • Studies show that there is a wide spread of vaccine misinformation on social media platforms.

 • Consuming anti vaccine social media content has the potential to negatively impact vaccine attitudes and uptake.


Anti-vaccine Misinformation and Social Media

 •YouTube is the largest video sharing social media platform.

 •The article describes YouTube as a hotbed for anti vaccine misinformation.

 •A study found that out of 172 human papillomavirus related videos on YouTube, only around 30% of the videos were pro-vaccine.

 •Another study showed that around 20% and 30% of videos on influenza and measles-mumps-rubella vaccines, were anti-vaccine videos.

 •According to both studies, anti-vaccine videos had more views than pro-vaccine videos


YouTube and Vaccine Misinformation

 •Filter bubbles are created by YouTube as viewers are exposed to content that is similar, repetitive and biased. 

 •The study wishes to explore to what degree YouTube’s recommendation algorithm shapes the exposure of people to vaccine related information and misinformation.


Goal of the Study


 • How do traditional media users and social media users in the US differ in their belief in vaccine misinformation?

• How does the acceptance or rejection of common vaccine misinformation relate to the trust an individual has in medical experts/expertise?


Questions of Research (type of media used and trust in medical expertise)


The researchers created two search networks from pro-vaccine and anti-vaccine keywords to resemble goal-oriented browsing (based on keyword search). In contrast to the goal-oriented browsing networks, they constructed two seed networks (resembling direct navigation) based on conspiracy and anti-vaccine expert seed videos. Video contents and network structures were analyzed using the network exposure model.

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