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

JMIR Theme Issue: COVID-19 Special Issue (2461) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1667) Infodemiology and Infoveillance (1369) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050)

Published on in Vol 24, No 10 (2022): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40323, first published .
Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis

Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis

Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis

Authors of this article:

Hassan Alhuzali1 Author Orcid Image ;   Tianlin Zhang2 Author Orcid Image ;   Sophia Ananiadou2, 3 Author Orcid Image
Article Authors Cited by (17) Tweetations (14) Metrics

Hassan Alhuzali   1 * , PhD ;   Tianlin Zhang   2 * , MSc ;   Sophia Ananiadou   2, 3 , PhD

1 College of Computers and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia

2 Department of Computer Science, National Centre for Text Mining, The University of Manchester, Manchester, United Kingdom

3 The Alan Turing Institute, London, United Kingdom

*these authors contributed equally

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