Tao Hu1, Siqin Wang2, Wei Luo3, Mengxi Zhang4, Xiao Huang5, Yingwei Yan3, Regina Liu6, Kelly Ly7, Viraj Kacker8, Bing She9, Zhenlong Li10. 1. Harvard University, Cambridge, US. 2. University of Queensland, Brisbane, AU. 3. National University of Singapore, 21 Lower Kent Ridge Rd, Singapore, SG. 4. Ball State University, Muncie, US. 5. University of Arkansas, Fayetteville, US. 6. Mercer University, Macon, US. 7. University of Massachusetts Lowell, Lowell, US. 8. Georgia Institute of Technology, GA, US. 9. University of Michigan, Ann Arbor, US. 10. University of South Carolina, SC, US.
Abstract
BACKGROUND: The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the United States and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, public health officials, and policy makers to understand public attitudes and opinions towards vaccines, such that effective interventions and educational campaigns can be designed to promote vaccine acceptance. OBJECTIVE: The aim of this study is to investigate public opinion and perception on COVID-19 vaccines in the US. We investigated the spatiotemporal trends of public sentiment and emotion towards COVID-19 vaccines, and analyzed how such trends relate to popular topics found on Twitter. METHODS: We collected over 300,000 geotagged tweets in the US from March 1, 2020 to February 28, 2021. We examined the spatiotemporal patterns of public sentiment and emotion over time at both national and state scales and identified three phases along the pandemic timeline with the sharp changes in public sentiment and emotion. Using sentiment analysis, emotion analysis (with cloud mapping of keywords), and topic modelling, we further identified 11 key events and major topics as the potential drivers to such changes. RESULTS: An increasing trend of positive sentiment in conjunction with the decrease in negative sentiment are generally observed in most states, reflecting the rising confidence and anticipation of the public towards vaccines. The overall tendency of the eight types of emotion implies that the public trusts and anticipates the vaccine. This is accompanied by a mixture of fear, sadness and anger. Critical social/international events and/or the announcements from political leaders and authorities may have potential impacts on the public opinion towards vaccines. These factors help identify underlying themes and validate insights from the analysis. CONCLUSIONS: The analyses of near real-time social media big data benefit public health authorities by enabling them to monitor public attitudes and opinions towards vaccine-related information in a geo-aware manner, address the concerns of vaccine skeptics, and promote the confidence that individuals within a certain region or community have towards vaccines.
BACKGROUND: The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the United States and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, public health officials, and policy makers to understand public attitudes and opinions towards vaccines, such that effective interventions and educational campaigns can be designed to promote vaccine acceptance. OBJECTIVE: The aim of this study is to investigate public opinion and perception on COVID-19 vaccines in the US. We investigated the spatiotemporal trends of public sentiment and emotion towards COVID-19 vaccines, and analyzed how such trends relate to popular topics found on Twitter. METHODS: We collected over 300,000 geotagged tweets in the US from March 1, 2020 to February 28, 2021. We examined the spatiotemporal patterns of public sentiment and emotion over time at both national and state scales and identified three phases along the pandemic timeline with the sharp changes in public sentiment and emotion. Using sentiment analysis, emotion analysis (with cloud mapping of keywords), and topic modelling, we further identified 11 key events and major topics as the potential drivers to such changes. RESULTS: An increasing trend of positive sentiment in conjunction with the decrease in negative sentiment are generally observed in most states, reflecting the rising confidence and anticipation of the public towards vaccines. The overall tendency of the eight types of emotion implies that the public trusts and anticipates the vaccine. This is accompanied by a mixture of fear, sadness and anger. Critical social/international events and/or the announcements from political leaders and authorities may have potential impacts on the public opinion towards vaccines. These factors help identify underlying themes and validate insights from the analysis. CONCLUSIONS: The analyses of near real-time social media big data benefit public health authorities by enabling them to monitor public attitudes and opinions towards vaccine-related information in a geo-aware manner, address the concerns of vaccine skeptics, and promote the confidence that individuals within a certain region or community have towards vaccines.
Authors: Abolfazl Mollalo; Alireza Mohammadi; Sara Mavaddati; Behzad Kiani Journal: Int J Environ Res Public Health Date: 2021-11-16 Impact factor: 3.390