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

Development and Evaluation of Research Methods, Instruments and Tools (646) JMIR Theme Issue: COVID-19 Special Issue (2500) Outbreak and Pandemic Preparedness and Management (1783) Digital Contact Tracing, Digital Proximity Tracing, Precision Public Health (153) Theme Issue: Apps for COVID-19 (#Apps4Covid) (139) Natural Language Processing (806)

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
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Global User-Level Perception of COVID-19 Contact Tracing Applications: A Data-Driven Approach Using Natural Languag… https://t.co/cmmKyVK8EA

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JMIR Formative Res: Global User-Level Perception of #covid19 Contact Tracing Applications: Data-Driven Approach Usi… https://t.co/6H4Ki1iaxv

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RT @jmirpub: JMIR Formative Res: Global User-Level Perception of #covid19 Contact Tracing Applications: Data-Driven Approach Using Natural…

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