A Chronological and Geographical Analysis of Personal Reports of COVID-19 on Twitter.

ABSTRACT: The rapidly evolving outbreak of COVID-19 presents challenges for actively monitoring its spread. In this study, we assessed a social media mining approach for automatically analyzing the chronological and geographical distribution of users in the United States reporting personal information related to COVID-19 on Twitter. The results suggest that our natural language processing and machine learning framework could help provide an early indication of the spread of COVID-19.

SUBMITTER: Klein AZ 

PROVIDER: S-EPMC7276035 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature