A curated collection of COVID-19 online datasets
Isa Inuwa-Dutse, Ioannis Korkontzelos

TL;DR
This paper presents a curated collection of COVID-19 online datasets, including Twitter data, credible information sources, and global reports, to aid research in combating misinformation and understanding the pandemic.
Contribution
It introduces an extensive curated dataset collection specifically aimed at supporting COVID-19 misinformation research and pandemic analysis.
Findings
Provides access to diverse COVID-19 datasets
Facilitates research on misinformation and pandemic trends
Suggests research problems using the datasets
Abstract
One of the defining moments of the year 2020 is the outbreak of Coronavirus Disease (Covid-19), a deadly virus affecting the body's respiratory system to the point of needing a breathing aid via ventilators. As of June 21, 2020 there are 12,929,306 confirmed cases and 569,738 confirmed deaths across 216 countries, areas or territories. The scale of spread and impact of the pandemic left many nations grappling with preventive and curative approaches. The infamous lockdown measure introduced to mitigate the virus spread has altered many aspects of our social routines in which demand for online-based services skyrocketed. As the virus propagate, so does misinformation and fake news around it via online social media, which seems to favour virality over veracity. With a majority of the populace confined to their homes for a long period, vulnerability to the toxic impact of online…
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Taxonomy
TopicsMisinformation and Its Impacts · COVID-19 diagnosis using AI · Complex Network Analysis Techniques
