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

Theme Issue: Social Media, Ethics, and COVID-19 Misinformation (34) JMIR Theme Issue: COVID-19 Special Issue (2394) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1015) Infodemiology and Infoveillance (1278) Natural Language Processing (650)

Published on in Vol 24, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37142, first published .
Exploring COVID-19–Related Stressors: Topic Modeling Study

Exploring COVID-19–Related Stressors: Topic Modeling Study

Exploring COVID-19–Related Stressors: Topic Modeling Study

Authors of this article:

Yue Tong Leung1 Author Orcid Image ;   Farzad Khalvati1, 2, 3, 4 Author Orcid Image
Article Authors Cited by (7) Tweetations (4) Metrics

Journals

  1. Roh M, Choi Y, Park H. Analysis of Issues in Fitness Centers through News Articles before and after the COVID-19 Pandemic in South Korea: Applying Big Data Analysis. Sustainability 2023;15(3):2660 View
  2. Yao L, Ferawati K, Liew K, Wakamiya S, Aramaki E. Disruptions in the Cystic Fibrosis Community’s Experiences and Concerns During the COVID-19 Pandemic: Topic Modeling and Time Series Analysis of Reddit Comments. Journal of Medical Internet Research 2023;25:e45249 View
  3. Golos A, Guntuku S, Piltch-Loeb R, Leininger L, Simanek A, Kumar A, Albrecht S, Dowd J, Jones M, Buttenheim A, Taskin N. Dear Pandemic: A topic modeling analysis of COVID-19 information needs among readers of an online science communication campaign. PLOS ONE 2023;18(3):e0281773 View
  4. Smail B, Aliane H, Abdeldjalil O. Using an explicit query and a topic model for scientific article recommendation. Education and Information Technologies 2023;28(12):15657 View
  5. Gu D, Liu H, Zhao H, Yang X, Li M, Liang C. A deep learning and clustering‐based topic consistency modeling framework for matching health information supply and demand. Journal of the Association for Information Science and Technology 2024;75(2):152 View
  6. King J, McQuaid A, Leeson V, Tella O, Crawford M. Characterising subgroups of people with severe COVID anxiety by latent profile analysis. Journal of Affective Disorders 2024;344:115 View
  7. Ruocco L, Zhuang Y, Ng R, Munthali R, Hudec K, Wang A, Vereschagin M, Vigo D. A platform for connecting social media data to domain-specific topics using large language models: an application to student mental health. JAMIA Open 2024;7(1) View