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

点击翻译按钮获取中文摘要

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.