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Limited Role of Bots in Spreading Vaccine-Critical Information Among Active Twitter Users in the United States: 2017-2019. | LitMetric

Limited Role of Bots in Spreading Vaccine-Critical Information Among Active Twitter Users in the United States: 2017-2019.

Am J Public Health

Adam G. Dunn and Jason Dalmazzo are with the Discipline of Biomedical Informatics and Digital Health, University of Sydney, Sydney, Australia. Didi Surian, Maryke Steffens, Amalie Dyda, and Enrico Coiera are with the Centre for Health Informatics, Macquarie University, Sydney, Australia. Dana Rezazadegan is with the Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne, Australia. Julie Leask is with the Susan Wakil School of Nursing and Midwifery, University of Sydney, Sydney, Australia. Aditi Dey is with the National Centre for Immunisation Research and Surveillance, University of Sydney, Sydney, Australia. Kenneth D. Mandl is with the Computational Health Informatics Program, Boston Children's Hospital, Boston, MA.

Published: October 2020

To examine the role that bots play in spreading vaccine information on Twitter by measuring exposure and engagement among active users from the United States. We sampled 53 188 US Twitter users and examined who they follow and retweet across 21 million vaccine-related tweets (January 12, 2017-December 3, 2019). Our analyses compared bots to human-operated accounts and vaccine-critical tweets to other vaccine-related tweets. The median number of potential exposures to vaccine-related tweets per user was 757 (interquartile range [IQR] = 168-4435), of which 27 (IQR = 6-169) were vaccine critical, and 0 (IQR = 0-12) originated from bots. We found that 36.7% of users retweeted vaccine-related content, 4.5% retweeted vaccine-critical content, and 2.1% retweeted vaccine content from bots. Compared with other users, the 5.8% for whom vaccine-critical tweets made up most exposures more often retweeted vaccine content (62.9%; odds ratio [OR] = 2.9; 95% confidence interval [CI] = 2.7, 3.1), vaccine-critical content (35.0%; OR = 19.0; 95% CI = 17.3, 20.9), and bots (8.8%; OR = 5.4; 95% CI = 4.7, 6.3). A small proportion of vaccine-critical information that reaches active US Twitter users comes from bots.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532316PMC
http://dx.doi.org/10.2105/AJPH.2020.305902DOI Listing

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