Author: Bisanzio, Donal; Kraemer, Moritz U G; Brewer, Thomas; Brownstein, John S; Reithinger, Richard
Title: Geolocated Twitter social media data to describe the geographic spread of SARS-CoV-2 Cord-id: elq4rrdi Document date: 2020_7_23
ID: elq4rrdi
Snippet: Openly available, geotagged Twitter data from 2013 to 2015 was used to estimate the 2019–2020 human mobility patterns in and outside of China to predict the spatiotemporal spread of severe acute respiratory syndrome coronavirus 2. Countries with the highest number of visiting Twitter users outside of China were the USA, Japan, UK, Germany and Turkey. A high correlation was observed when comparing country-level Twitter user visits and reported cases.
Document: Openly available, geotagged Twitter data from 2013 to 2015 was used to estimate the 2019–2020 human mobility patterns in and outside of China to predict the spatiotemporal spread of severe acute respiratory syndrome coronavirus 2. Countries with the highest number of visiting Twitter users outside of China were the USA, Japan, UK, Germany and Turkey. A high correlation was observed when comparing country-level Twitter user visits and reported cases.
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