In Journal of medical Internet research ; h5-index 88.0
BACKGROUND : Global efforts towards the development and deployment of a vaccine for SARS-CoV-2 are rapidly advancing. To achieve herd immunity, widespread administration is required which necessitates significant cooperation from the general public. As such, it is crucial that governments and public health agencies understand public sentiment towards vaccines, which can help guide educational campaigns and other targeted policy interventions.
OBJECTIVE : The aim of this study was to develop and apply an artificial-intelligence (AI)-based approach to analyse social-media public sentiment in the United Kingdom (UK) and the United States (US) towards COVID-19 vaccinations, to better understand public attitude and identify topics of concern.
METHODS : Over 300,000 social-media posts related to COVID-19 vaccinations were extracted, including 23,571 Facebook-posts from the UK and 144,864 from the US, along with 40,268 tweets from the UK and 98,385 from the US respectively, from 1st March - 22nd November 2020. We used natural-language processing and deep learning-based techniques to predict average sentiments, sentiment trends and topics of discussion. These were analysed longitudinally and geo-spatially, and a manual-reading of randomly selected posts around points of interest helped identify underlying themes and validated insights from the analysis.
RESULTS : We found overall averaged positive, negative and neutral sentiment in the UK to be 58%, 22% and 17%, compared to 56%, 24% and 18% in the US, respectively. Public optimism over vaccine development, effectiveness and trials as well as concerns over safety, economic viability and corporation control were identified. We compared our findings to national surveys in both countries and found them to correlate broadly.
CONCLUSIONS : AI-enabled social-media analysis should be considered for adoption by institutions and governments, alongside surveys and other conventional methods of assessing public attitude. This could enable real-time assessment, at scale, of public confidence and trust in COVID-19 vaccinations, help address concerns of vaccine-sceptics and develop more effective policies and communication strategies to maximise uptake.
Hussain Amir, Tahir Ahsen, Hussain Zain, Sheikh Zakariya, Gogate Mandar, Dashtipour Kia, Ali Azhar, Sheikh Aziz