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

Formative Evaluation of Digital Health Interventions (1752) JMIR Theme Issue: COVID-19 Special Issue (2244) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1386) Outbreak and Pandemic Preparedness and Management (1530) Infectious Diseases (non-STD/STI) (1289) Digital Contact Tracing, Digital Proximity Tracing, Precision Public Health (127) Surveillance Systems (391) Participatory Epidemiology and Surveillance (97)

Published on in Vol 6 , No 3 (2022) :March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33314, first published .
Public Perception of the Use of Digital Contact-Tracing Tools After the COVID-19 Lockdown: Sentiment Analysis and Opinion Mining

Public Perception of the Use of Digital Contact-Tracing Tools After the COVID-19 Lockdown: Sentiment Analysis and Opinion Mining

Public Perception of the Use of Digital Contact-Tracing Tools After the COVID-19 Lockdown: Sentiment Analysis and Opinion Mining

Authors of this article:

Zhilian Huang 1 Author Orcid Image ;   Evonne Tay 1 Author Orcid Image ;   Dillon Wee 1 Author Orcid Image ;   Huiling Guo 1 Author Orcid Image ;   Hannah Yee-Fen Lim 2 Author Orcid Image ;   Angela Chow 1, 3 Author Orcid Image
Article Authors Cited by (2) Tweetations (14) Metrics

Journals

  1. Pucci F, Fedele P, Dimitri G. Speech emotion recognition with artificial intelligence for contact tracing in the COVID‐19 pandemic. Cognitive Computation and Systems 2023;5(1):71 View