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Pandemic Pulse: Unraveling and Modeling Social Signals during the COVID-19 Pandemic

2020/06/10 by Steven J. Krieg, Krieg, Steven J., Jennifer J. Schnur +7
Mathematics · Social Sciences · #COVID-19 epidemiological studies #Computational and Text Analysis Methods #Computers and Society (cs.CY) #FOS: Computer and information sciences #Media Influence and Politics #Misinformation and Its Impacts #Social Media and Politics #Social and Information Networks (cs.SI)

paper · pdf · doi:10.48550/arxiv.2006.05983

openalex publication_date 2020/06/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We present and begin to explore a collection of social data that represents part of the COVID-19 pandemic's effects on the United States. This data is collected from a range of sources and includes longitudinal trends of news topics, social distancing behaviors, community mobility changes, web searches, and more. This multimodal effort enables new opportunities for analyzing the impacts such a pandemic has on the pulse of society. Our preliminary results show that the number of COVID-19-related news articles published immediately after the World Health Organization declared the pandemic on March 11, and that since that time have steadily decreased---regardless of changes in the number of cases or public policies. Additionally, we found that politically moderate and scientifically-grounded sources have, relative to baselines measured before the beginning of the pandemic, published a lower proportion of COVID-19 news than more politically extreme sources. We suggest that further analysis of these multimodal signals could produce meaningful social insights and present an interactive dashboard to aid further exploration.

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