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 was to investigate public opinion and perception on COVID-19 vaccines in the United States. 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 United States 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 3 phases along the pandemic timeline with sharp changes in public sentiment and emotion. Using sentiment analysis, emotion analysis (with cloud mapping of keywords), and topic modeling, we further identified 11 key events and major topics as the potential drivers to such changes. Results An increasing trend in positive sentiment in conjunction with a decrease in negative sentiment were generally observed in most states, reflecting the rising confidence and anticipation of the public towards vaccines. The overall tendency of the 8 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 or international events or announcements by political leaders and authorities may have potential impacts on 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.

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in 26 journals in the GIScience community. Only the journals included in the Science Citation Index (SCI), Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Emerging Sources Citation Index (ESCI) are included. The four indices are among the core collections of Web of Science according to Clarivate Analytics (http://mjl.clarivate.com/). The journals focus more on remote sensing and photogrammetry (e.g., ISPRS Journal of Photogrammetry and Remote Sensing) are not included because this review focuses on publications upon GIS.The keyword 'VGI' instead of 'volunteered geographic information' is used for the search of articles about volunteered geographic information (VGI). Thus, articles in which the term 'volunteered geographic information' is unabbreviated (a lowfrequency term) are not included in this review, which are considered of minor relevance to VGI. Other terms related to VGI (e.g., user-generated content, social media, and neogeography) are not used as keywords for the literature search, as this review focuses on VGI as the primary perspective or point of research. The keyword 'VGI' serves as a central point ('seed') for us to identify other terms (perspectives) related to VGI from articles involving the term 'VGI'. Except for GIScience & Remote Sensing and Journal of Geographical Systems, all the remaining 24 journals have returned articles involving the term 'VGI'. Only research articles and review articles are retrieved. Other contributions such as commentaries, editorials, project reports, or communications are excluded. Articles in which 'VGI' is not the abbreviation of 'volunteered geographic information' are ignored. This results in 374 articles.From these 374 articles, we have further manually removed 28 articles in which VGI plays a minor role, e.g., VGI is briefly mentioned in the discussion (Frazier et al. (2018) or is a related topic rather than the focus (Brovelli et al. (2015). The article filtering process results in 346 articles (326 research articles and 20 review articles) in which VGI is the main topic of exploration or at least is used as a source of data. Each of the 20 review articles is about a sub-topic of VGI, such as VGI quality assessment methods (Senaratne et al. 2017) and VGI for natural hazards (Klonner et al. 2016); none provides a comprehensive review and is thus treated as the input in the analysis of this review.