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

Infoveillance and Social Listening (209) JMIR Theme Issue: COVID-19 Special Issue (2452) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641)

Published on in Vol 2, No 2 (2022): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39849, first published .
Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media

Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media

Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media

Authors of this article:

Amélia Déguilhem1 Author Orcid Image ;   Joelle Malaab1 Author Orcid Image ;   Manissa Talmatkadi1 Author Orcid Image ;   Simon Renner1 Author Orcid Image ;   Pierre Foulquié1 Author Orcid Image ;   Guy Fagherazzi2 Author Orcid Image ;   Paul Loussikian1 Author Orcid Image ;   Tom Marty1 Author Orcid Image ;   Adel Mebarki1 Author Orcid Image ;   Nathalie Texier1 Author Orcid Image ;   Stephane Schuck1 Author Orcid Image
Article Authors Cited by (9) Tweetations (9) Metrics

Amélia Déguilhem   1 * , MSc ;   Joelle Malaab   1 * , MSc, MPH ;   Manissa Talmatkadi   1 , MSc ;   Simon Renner   1 , PharmD ;   Pierre Foulquié   1 , MSc ;   Guy Fagherazzi   2 , PhD ;   Paul Loussikian   1 , MSc ;   Tom Marty   1 , PharmD ;   Adel Mebarki   1 , MSc ;   Nathalie Texier   1 , PharmD ;   Stephane Schuck   1 , MD

1 Kap Code, Paris, France

2 Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg

*these authors contributed equally

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