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

Journal: Journal of medical Internet research
Published Date: Jan 22, 2021

Abstract

BACKGROUND: In the United States, the rapidly evolving COVID-19 outbreak, the shortage of available testing, and the delay of test results present challenges for actively monitoring its spread based on testing alone.

Authors

  • Ari Z Klein
    Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Arjun Magge
    Health Language Processing Center, Institute for Biomedical Informatics at the Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
  • Karen O'Connor
    Department of Biomedical Informatics, Arizona State University, Scottsdale, AZ, USA.
  • Jesus Ivan Flores Amaro
    Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
  • Davy Weissenbacher
    Health Language Processing Center, Institute for Biomedical Informatics at the Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
  • Graciela Gonzalez Hernandez
    Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

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