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

Published: 10 December 2020 Publication History

Abstract

COVID-19 has presented society with a unique set of challenges, including seeking a scientific understanding of the novel coronavirus, modeling its epidemiology, and inferring appropriate societal response. In this article, we posit that fighting a pandemic is as much a social endeavor as a medicinal and scientific one and focus on developing a platform for understand the social pulse of the United States during the COVID-19 crisis. We collected a multitude of data that includes longitudinal trends of news topics, social distancing behaviors, community mobility changes, web searches, and other descriptors of the COVID-19 pandemic’s effects on the United States. 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 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 articles than more politically extreme sources—a fact that has implications for the spread and consequences of misinformation during the pandemic. We suggest that further analysis of these multi-modal signals could produce meaningful social insights and present an interactive dashboard to aid further exploration.1

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  1. Pandemic Pulse: Unraveling and Modeling Social Signals During the COVID-19 Pandemic

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    cover image Digital Government: Research and Practice
    Digital Government: Research and Practice  Volume 2, Issue 2
    COVID-19 Commentaries and Case Study
    April 2021
    119 pages
    EISSN:2639-0175
    DOI:10.1145/3442345
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

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    Publication History

    Published: 10 December 2020
    Online AM: 06 November 2020
    Accepted: 01 October 2020
    Revised: 01 October 2020
    Received: 01 July 2020
    Published in DGOV Volume 2, Issue 2

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    Author Tags

    1. Covid-19
    2. coronavirus
    3. mobility trends
    4. news data
    5. political bias
    6. sars-cov-2
    7. social distancing
    8. social signals

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