Researchers at the University of Waterloo examined 81 published articles examining social media during the pandemic, with more than half assessing Twitter posts.

“All media tend to see increased use when an emergency occurs, but social media is the easiest to turn to and engage in when an event like a pandemic breaks out,” said Zahid Butt, a professor in the School of Public Health and Health Systems. “And because the content is user-generated, it is also easy to present inaccuracies or subjective information, going so far as unchecked conspiracy theories.”

Some examples that highlighted the misinformation include studies examining YouTube videos. One of them analyzed the top 100 YouTube videos with the most views from January 2020 and found that fewer than 33 included any of the key recommended behaviours for COVID containment. Another study from South Korea showed that misleading videos made up almost 40 per cent of the most-watched videos and had more likes and longer viewing times than did useful videos.

Misinformation was also prevalent on Twitter. One study analyzed 12 million tweets from the U.S. and 15 million from the Philippines in March, and both countries showed a positive link between bot activities and the rate of hate speech in dense, isolated communities. However, another study analyzed 942 tweets that showed that although there were more tweets with false information, they also had fewer retweets and lower engagement than those containing scientific evidence or factual statements.

“Social media has an increasingly important role to play in health education and the understanding of policy,” Butt said. “What this review shows us is that public health organizations and governments need to be present and active on social media platforms in order to guard against misinformation.”

What social media told us in the time of COVID-19: A scoping review” was published in The Lancet Digital Health, and authored by Shu-Feng Tsao (Waterloo), Helen Chen (Waterloo), Therese Tisseverasinghe (Seneca College), Yang Yang (Waterloo), Lianghua Li (Waterloo) and Zahid Butt (Waterloo).

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