RAPID: Analyses of Emotions Expressed in Social Media and Forums During the COVID-19 Pandemic

调查人员正在构建一个全面的数据库，收集、存储和分析来自社交媒体和网络论坛的与COVID-19相关的恐惧、焦虑、悲伤和愤怒的内容。先前的文献已经证明，压力可以降低决策能力和质量。在线风险（例如，隐私、安全漏洞）可能有所增加，因为社交媒体和基于网络的论坛已成为主要的通信形式。 该数据集将建立与位置和时间相关的情绪记录，这些情绪可能与虚拟威胁的脆弱性增加有关。这些数据将允许对风险进行分析，例如在线共享更多个人信息，错误信息的发起和传播，放松的安全偏好以及内部威胁。第二个目标是回答关于这一流行病期间经历的负面情绪与区域差异和社会经济地位之间联系的基本研究问题。鉴于许多在线数据源不存档数据或提供档案供分析，这项研究是紧迫和及时的。该研究通过分析和理解流行期间情绪如何与当地和区域社会和地理指标联系起来，为流行期间的社区反应和政策制定提供信息，从而推动科学发展。研究团队将从2019年12月31日至2020年12月31日收集10-15个社交媒体和网络论坛的COVID-19数据。数据收集将从中国当局首次治疗后来被称为冠状病毒的肺炎病例时开始开始。调查人员将跟踪对COVID-19的反应一年，以评估公众对大流行的情绪反应。为了研究各地区的健康和经济差异，调查人员将分析地理位置的职位，并将数据与人口普查局调查的变量相结合。人工智能和数据科学技术将用于处理和分析在这项工作中收集的大量异构数据。根据这些分析，可以制定政策，以改善预防，安全，隐私和其他公众的理解和政策在大流行期间。这个奖项反映了NSF的法定使命，并已被认为是值得支持的评估使用基金会的知识价值和更广泛的影响审查标准。

The investigators are constructing a comprehensive database that collects, stores, and analyzes content related to fear, anxiety, sadness, and anger associated with COVID-19 from social media and web-based forums. Prior literature has demonstrated that stress can reduce decision making capacity and quality. Online risks (e.g., privacy, security vulnerabilities) may have increased as social media and web-based forums have become a predominant form of communication. This dataset will establish a location- and time-linked record of emotions that may be associated with increased vulnerability to virtual threats. The data will permit analyses of risks such as sharing of more personal information online, misinformation initiation and spread, relaxed security preferences, and insider threat. A second goal is to answer fundamental research questions about the linkages of negative emotions experienced during this pandemic with regional variation and socioeconomic status. This research is urgent and timely given that many online data sources do not archive data or make archives available for analyses. This research advances science by informing community response and policymaking during pandemics through an analysis and understanding of how emotions are linked to local and regional social and geographic indicators during the pandemic.The research team will collect COVID-19 data from 10-15 social media and web-based forums from December 31, 2019 to December 31, 2020. Data collection will begin when Chinese authorities first treated pneumonia cases that later became known as the coronavirus. The investigators will follow responses to COVID-19 for a year to assess the public's emotional responses to the pandemic. To examine health and economic disparities by region, the investigators will analyze geolocated posts and integrate the data with variables from the Census Bureau Survey. Artificial intelligence and data science techniques will be used in processing and analyzing the large amounts of heterogenous data collected in this effort. From these analyses, policies could be created to improve prevention, security, privacy and other public understanding and policies during the pandemic.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.