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Extending A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter to England, UK

Authors :
S Golder
Ari Z. Klein
Arjun Magge
Karen O’Connor
Haitao Cai
Davy Weissenbacher
Graciela Gonzalez-Hernandez
Source :
medRxiv, article-version (status) pre, article-version (number) 1
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

The rapidly evolving COVID-19 pandemic presents challenges for actively monitoring its transmission. In this study, we extend a social media mining approach used in the US to automatically identify personal reports of COVID-19 on Twitter in England, UK. The findings indicate that natural language processing and machine learning framework could help provide an early indication of the chronological and geographical distribution of COVID-19 in England.

Details

Language :
English
Database :
OpenAIRE
Journal :
medRxiv
Accession number :
edsair.doi.dedup.....77aa857aa837e0b4ada6cbbebe4ec120