51成人动漫

Through the use of social media, celebrities and other people in the public eye helped to shape the public discourse and opinions on the COVID-19 pandemic and public health efforts, according to an analysis of over 45,000 tweets posted from January 2020 to March 2022.

While there were small differences in sentiment observed, a "broadly polarized negative tone" was noted among certain public figures who shared a consistent pattern of emotional content related to their risk perceptions, political ideologies, and health-protective behaviors, reported Arash Shaban-Nejad, MPH, PhD, of the University of Tennessee Health Science Center in Memphis, and co-authors.

During these first 2 years of the pandemic, tweets by well-known figures such as Joe Rogan, Eric Clapton, and former President Donald Trump included mostly negative sentiments about COVID vaccines and other public health measures like masking, with tweets showing a clear pattern of increasing negativity over time, the authors noted in .

Notably, posts shared by politicians and news anchors, such as Tucker Carlson, appeared to have the greatest influence on the public.

"The risk of severe negative health outcomes increases with failure to comply with health-protective behavior recommendations set forth by public health officials," Shaban-Nejad told 51成人动漫. "Our findings suggest that polarized messages from societal elites may downplay these risks."

"Clinically, negative perceptions of COVID-19 have given rise to vaccine hesitancy and vaccine refusal in the U.S. and other populations," he added. "The less-than-ideal vaccination rates led to avoidable illnesses, comorbidities, and increased deaths."

Analysis of social media activity could be used by public health officials and policy makers to fight misinformation on platforms like Twitter, the researchers said, pointing out that more data-driven communication efforts could bolster infection prevention and control initiatives for COVID or potential future disease outbreaks.

"Health professionals and public health organizations, in partnership with other community groups, must proactively and efficiently use technology and media to share clear health messages in accessible language, disseminate correct information, develop and advocate nonpartisan public health policies, and inform [and] educate the public about misinformation," said Shaban-Nejad.

Katrine Wallace, PhD, an epidemiologist at the University of Illinois-Chicago School of Public Health, has developed her own social media presence pushing back against mis- and disinformation. She told 51成人动漫 that this research adds evidence to a trend that she has personally witnessed over the last several years.

"I can tell you that from my own anecdotal experience, but to have some data to actually say, 'Look, this is proven now' -- that is powerful because it shows that our anecdotal experience is really happening," noted Wallace, who was not involved in the study.

Wallace said that the focus of the analysis on 12 public figures -- also including Nicki Minaj, Aaron Rodgers, Novak Djokovic, Rand Paul, Phil Valentine, Ted Cruz, Candace Owens, and Ron DeSantis -- was a great first step, but these people are not the true source of the misinformation that she has seen throughout the pandemic, though they play a role in spreading the misinformation to very large audiences.

"The real issue is that this information doesn't start with them," she explained. "This information starts with the more medical misinformation spreaders like Robert Malone and Peter McCullough, and then it gets disseminated by the Joe Rogans."

"I see them as being like a conduit, a big platform to then platform this medical misinformation, but I don't think it starts with them," she stressed.

For this analysis, Shaban-Nejad and colleagues looked at approximately 13 million tweets. After excluding posts from suspected bots or highly repetitive accounts, they then searched for posts that mentioned COVID vaccine-related terms and the names of one of those 12 public figures together. The final dataset included 45,255 tweets posted by 34,407 unique users.

They used an AI model called DistilRoBERTa, using a team of five researchers who manually labeled about 4,000 tweets as either positive or negative based on its sentiment toward COVID vaccines. Those labeled tweets were used to train the AI model to recognize sentiment of the overall dataset.

Shaban-Nejad and team noted that more analysis should be done to determine the correlation between negative sentiments shared by public figures and specific "monumental events" that occurred during the pandemic, such as the authorization of the vaccines, adding that finding that connection could help "revolutionize" responses to future disease outbreaks.

Wallace agreed that more research in this area would be critical in effectively fighting misinformation in future outbreaks, which she noted could be a matter of life or death.

"Most people who died of COVID after the vaccines were available died as a direct result of misinformation," she said.

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