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

Infodemic Management (54) Innovative Methods in Public Health and Surveillance (357) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1766) Infodemiology and Infoveillance (1440) Public (e)Health, Digital Epidemiology and Public Health Informatics (844) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1529) Outbreak and Pandemic Preparedness and Management (1777) Cost-Effectiveness and Economics (285) GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (120)

Published on in Vol 5 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58539, first published .
Geosocial Media’s Early Warning Capabilities Across US County-Level Political Clusters: Observational Study

Geosocial Media’s Early Warning Capabilities Across US County-Level Political Clusters: Observational Study

Geosocial Media’s Early Warning Capabilities Across US County-Level Political Clusters: Observational Study

Authors of this article:

Dorian Arifi1, 2 Author Orcid Image ;   Bernd Resch1, 2, 3 Author Orcid Image ;   Mauricio Santillana4, 5 Author Orcid Image ;   Weihe Wendy Guan3 Author Orcid Image ;   Steffen Knoblauch6, 7, 8 Author Orcid Image ;   Sven Lautenbach6, 8 Author Orcid Image ;   Thomas Jaenisch9, 10 Author Orcid Image ;   Ivonne Morales10, 11 Author Orcid Image ;   Clemens Havas12 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Resch B, Kolokoussis P, Hanny D, Brovelli M, Kamel Boulos M. The generative revolution: AI foundation models in geospatial health—applications, challenges and future research. International Journal of Health Geographics 2025;24(1) View
  2. Serere H, Resch B. Dynamic Named Entity Recognition model to distinguish authors’ positions relative to mentioned locations. Geomatica 2025;77(1):100055 View