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

Infodemiology and Infoveillance (1558) Outbreak and Pandemic Preparedness and Management (1826) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139) Infectious Diseases (non-STD/STI) (1726) COVID-19 Vaccination (179) Vaccination Sentiment and Anti-Vaccination Infodemiology (90) Infoveillance and Social Listening (313) Social Media in Public Health informatics (67)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59425, first published .
Long COVID Discourse in Canada, the United States, and Europe: Topic Modeling and Sentiment Analysis of Twitter Data

Long COVID Discourse in Canada, the United States, and Europe: Topic Modeling and Sentiment Analysis of Twitter Data

Long COVID Discourse in Canada, the United States, and Europe: Topic Modeling and Sentiment Analysis of Twitter Data

Authors of this article:

Ahmed Ghassan Tawfiq AbuRaed1 Author Orcid Image ;   Emil Azuma Prikryl2 Author Orcid Image ;   Giuseppe Carenini1 Author Orcid Image ;   Naveed Zafar Janjua3 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Khakban I, Jain S, Gallab J, Dharmaraj B, Zhou F, Lokker C, Abdelkader W, Zeraatkar D, Busse J. Impact of the COVID-19 Pandemic and the 2021 National Institute for Health and Care Excellence Guidelines on Public Perspectives Toward Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Thematic and Sentiment Analysis on Twitter (Rebranded as X). Journal of Medical Internet Research 2025;27:e65087 View
  2. Hameed S, Nauman M, Akhtar N, Fayyaz M, Nawaz R. Explainable AI-driven depression detection from social media using natural language processing and black box machine learning models. Frontiers in Artificial Intelligence 2025;8 View