This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2388) Infodemiology and Infoveillance (1269) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552) Natural Language Processing (636) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010) Outbreak and Pandemic Preparedness and Management (1673)

Published on in Vol 23, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25314, first published .
Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set

Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set

Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set

Authors of this article:

Ari Z Klein1 Author Orcid Image ;   Arjun Magge1 Author Orcid Image ;   Karen O'Connor1 Author Orcid Image ;   Jesus Ivan Flores Amaro1 Author Orcid Image ;   Davy Weissenbacher1 Author Orcid Image ;   Graciela Gonzalez Hernandez1 Author Orcid Image
Article Authors Cited by (37) Tweetations (23) Metrics

Ari Z Klein   1 , PhD ;   Arjun Magge   1 , PhD ;   Karen O'Connor   1 , MS ;   Jesus Ivan Flores Amaro   1 , BS ;   Davy Weissenbacher   1 , PhD ;   Graciela Gonzalez Hernandez   1 , PhD

1 Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

Corresponding Author:

  • Ari Z Klein, PhD
  • Department of Biostatistics, Epidemiology, and Informatics
  • Perelman School of Medicine
  • University of Pennsylvania
  • 421A Blockley Hall
  • 423 Guardian Dr
  • Philadelphia, PA, 19104
  • United States
  • Phone: 1 215-746-1101
  • Email: ariklein@pennmedicine.upenn.edu