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

JMIR Theme Issue: COVID-19 Special Issue (2452) Infodemiology and Infoveillance (1349) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Outbreak and Pandemic Preparedness and Management (1727) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517)

Published on in Vol 22, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://www.medrxiv.org/content/10.1101/2020.06.10.20127225v1, first published .
Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis

Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis

Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis

Authors of this article:

Eisa Alanazi1 Author Orcid Image ;   Abdulaziz Alashaikh2 Author Orcid Image ;   Sarah Alqurashi1 Author Orcid Image ;   Aued Alanazi1 Author Orcid Image
Article Authors Cited by (16) Tweetations (13) Metrics

Eisa Alanazi   1 , BSc, MSc, PhD ;   Abdulaziz Alashaikh   2 , BEng, MSc, PhD ;   Sarah Alqurashi   1 , BSc ;   Aued Alanazi   1 , BSc

1 Center of Innovation and Development in Artificial Intelligence, Umm Al-Qura University, Makkah, Saudi Arabia

2 University of Jeddah, Jeddah, Saudi Arabia

Corresponding Author:

  • Eisa Alanazi, BSc, MSc, PhD
  • Center of Innovation and Development in Artificial Intelligence
  • Umm Al-Qura University
  • Prince Sultan Road
  • Makkah, 11343
  • Saudi Arabia
  • Phone: 966 55 601 4171
  • Email: eaanazi@uqu.edu.sa