AI analysis of social media posts can help gauge levels of public trust in, and skepticism of, COVID vaccination programs. Armed with such insights, local and national influencers could tailor promotional campaigns and policy interventions to boost vaccine buy-in.
So conclude researchers who applied natural language processing to tease out underlying attitudes and concerns behind more than 300,000 comments posted in 2020 by Facebook and Twitter users in the U.S. and U.K.
Combined, the two countries’ posters averaged 57% positive, 23% negative and 17.5% neutral sentiments toward COVID inoculation.
The authors stress that the project’s key achievement was demonstrating “the potential of AI-enabled real-time social media monitoring of public sentiments and attitudes to help detect and prevent [vaccine] fears and also to enable policymakers to understand the reasons why some social groups may be reluctant to be vaccinated against COVID-19.”
Such AI analyses, they add, “could enable real-time assessment, at scale, of public confidence and trust in COVID-19 vaccines, help address the concerns of vaccine skeptics, and help develop more effective policies and communication strategies to maximize uptake.”
The study was led by Amir Hussain, PhD, of Edinburgh Napier University. Senior author was Aziz Sheikh, MBBS, of the University of Edinburgh. Contributing from the U.S. was Azhar Ali, MBA, MBBS, of Harvard.
The Journal of Medical Internet Research published the work and has posted it in full for free.
Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.