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

JMIR Theme Issue: COVID-19 Special Issue (2452) Natural Language Processing (692) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Outbreak and Pandemic Preparedness and Management (1727) Machine Learning (1465) Artificial Intelligence (1371) Infodemiology and Infoveillance (1349) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (383) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Infectious Diseases (non-STD/STI) (1575) Hygiene and Infection Prevention (317) Anxiety and Stress Disorders (1053)

Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27341, first published .
Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence

Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence

Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence

Authors of this article:

Achini Adikari1 Author Orcid Image ;   Rashmika Nawaratne1 Author Orcid Image ;   Daswin De Silva1 Author Orcid Image ;   Sajani Ranasinghe1 Author Orcid Image ;   Oshadi Alahakoon2 Author Orcid Image ;   Damminda Alahakoon1 Author Orcid Image
Article Authors Cited by (32) Tweetations (10) Metrics

Achini Adikari   1 * , BSc ;   Rashmika Nawaratne   1 * , BSc, PhD ;   Daswin De Silva   1 * , BSc, PhD ;   Sajani Ranasinghe   1 * , BSc ;   Oshadi Alahakoon   2 * , BSc, PhD ;   Damminda Alahakoon   1 * , BSc, PhD

1 Research Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia

2 College of Engineering and Science, Victoria University, Melbourne, Australia

*all authors contributed equally

Corresponding Author: