Impact of COVID-19 Policies and Misinformation on Social Unrest
Martha Barnard (1), Radhika Iyer (1, 2), Sara Y. Del Valle (1),, Ashlynn R. Daughton (1) ((1) A-1 Information Systems, Modeling, Los Alamos, National Lab, Los Alamos, NM, USA, (2) Department of Political Science and, Department of Computing, Data Science, and Society

TL;DR
This study investigates how COVID-19 policies and misinformation influence social unrest across multiple regions, using diverse data sources to forecast protest activity with varying success.
Contribution
It introduces a multi-region, data-driven approach to predict protests during the pandemic, highlighting the predictive power and limitations of different data streams.
Findings
At least one data feature predicted protests in most regions.
Forecast accuracy varied significantly across countries.
Diverse data streams can help predict volatile social phenomena.
Abstract
The novel coronavirus disease (COVID-19) pandemic has impacted every corner of earth, disrupting governments and leading to socioeconomic instability. This crisis has prompted questions surrounding how different sectors of society interact and influence each other during times of change and stress. Given the unprecedented economic and societal impacts of this pandemic, many new data sources have become available, allowing us to quantitatively explore these associations. Understanding these relationships can help us better prepare for future disasters and mitigate the impacts. Here, we focus on the interplay between social unrest (protests), health outcomes, public health orders, and misinformation in eight countries of Western Europe and four regions of the United States. We created 1-3 week forecasts of both a binary protest metric for identifying times of high protest activity and the…
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Taxonomy
TopicsMisinformation and Its Impacts · Media Influence and Politics · COVID-19 epidemiological studies
