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

Infodemic Management (49) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1666) Infodemiology and Infoveillance (1369) Artificial Intelligence (1421) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Infoveillance and Social Listening (214)

Published on in Vol 3 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47317, first published .
Using Machine Learning Technology (Early Artificial Intelligence–Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID-19 Infodemic: Development and Implementation Study

Using Machine Learning Technology (Early Artificial Intelligence–Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID-19 Infodemic: Development and Implementation Study

Using Machine Learning Technology (Early Artificial Intelligence–Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID-19 Infodemic: Development and Implementation Study

Authors of this article:

Becky K White1 Author Orcid Image ;   Arnault Gombert2 Author Orcid Image ;   Tim Nguyen1 Author Orcid Image ;   Brian Yau1 Author Orcid Image ;   Atsuyoshi Ishizumi1 Author Orcid Image ;   Laura Kirchner2 Author Orcid Image ;   Alicia León2 Author Orcid Image ;   Harry Wilson2 Author Orcid Image ;   Giovanna Jaramillo-Gutierrez2 Author Orcid Image ;   Jesus Cerquides3 Author Orcid Image ;   Marcelo D’Agostino4 Author Orcid Image ;   Cristiana Salvi5 Author Orcid Image ;   Ravi Shankar Sreenath5 Author Orcid Image ;   Kimberly Rambaud5 Author Orcid Image ;   Dalia Samhouri6 Author Orcid Image ;   Sylvie Briand1 Author Orcid Image ;   Tina D Purnat1 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Becky K White   1 , PhD ;   Arnault Gombert   2 , MSc ;   Tim Nguyen   1 , MSc ;   Brian Yau   1 , BSc ;   Atsuyoshi Ishizumi   1 , MSc, MPH ;   Laura Kirchner   2 , MSc ;   Alicia León   2 , BA ;   Harry Wilson   2 , BA ;   Giovanna Jaramillo-Gutierrez   2 , PhD ;   Jesus Cerquides   3 , PhD ;   Marcelo D’Agostino   4 , MSc ;   Cristiana Salvi   5 , MS ;   Ravi Shankar Sreenath   5 , MBA ;   Kimberly Rambaud   5 , MSc ;   Dalia Samhouri   6 , MPH, PhD ;   Sylvie Briand   1 , MD, PhD ;   Tina D Purnat   1 , MSc

1 Department of Epidemic and Pandemic Preparedness and Prevention, World Health Organization, Geneva, Switzerland

2 Citibeats, Barcelona, Spain

3 Artificial Intelligence Research Institute, Spanish Council for Scientific Research, Cerdanyola, Spain

4 Information Systems for Health, Evidence and Intelligence for Action in Health, Pan American Health Organization and World Health Organization Regional Office for the Americas, Washington DC, DC, United States

5 Risk Communication and Community Engagement Unit, Health Emergencies Division, World Health Organization Regional Office for Europe, Copenhagen, Denmark

6 Country Health Emergency Preparedness and International Health Regulations (2005), World Health Organization Regional Office for Eastern Mediterranean, Cairo, Egypt

Corresponding Author:

  • Tina D Purnat, MSc
  • Department of Epidemic and Pandemic Preparedness and Prevention
  • World Health Organization
  • Ave Appia 21
  • Geneva, 1202
  • Switzerland
  • Phone: 41 227912111
  • Email: purnatt@who.int