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

Development and Evaluation of Research Methods, Instruments and Tools (511) JMIR Theme Issue: COVID-19 Special Issue (2461) Outbreak and Pandemic Preparedness and Management (1743) Digital Contact Tracing, Digital Proximity Tracing, Precision Public Health (148) Theme Issue: Apps for COVID-19 (#Apps4Covid) (137) Natural Language Processing (706)

Published on in Vol 6, No 5 (2022): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36238, first published .
Global User-Level Perception of COVID-19 Contact Tracing Applications: Data-Driven Approach Using Natural Language Processing

Global User-Level Perception of COVID-19 Contact Tracing Applications: Data-Driven Approach Using Natural Language Processing

Global User-Level Perception of COVID-19 Contact Tracing Applications: Data-Driven Approach Using Natural Language Processing

Authors of this article:

Kashif Ahmad1 Author Orcid Image ;   Firoj Alam2 Author Orcid Image ;   Junaid Qadir3 Author Orcid Image ;   Basheer Qolomany4 Author Orcid Image ;   Imran Khan5 Author Orcid Image ;   Talhat Khan5 Author Orcid Image ;   Muhammad Suleman5 Author Orcid Image ;   Naina Said5 Author Orcid Image ;   Syed Zohaib Hassan6 Author Orcid Image ;   Asma Gul7 Author Orcid Image ;   Mowafa Househ1 Author Orcid Image ;   Ala Al-Fuqaha1 Author Orcid Image
Article Authors Cited by (4) Tweetations (4) Metrics

Altmetric

Altmetric discovers Social Media mentions. Click the ‘See more details’ link for a full report.

Dimensions

Dimensions discovers Citations. Click the ‘details’ link for a full report.

Metrics Since Publication

Download .csv
Daily | Monthly | Annually