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

Cardiac Disease Management (156) JMIR Theme Issue: COVID-19 Special Issue (2554) Public (e)Health, Digital Epidemiology and Public Health Informatics (1008) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1911) Infodemiology and Infoveillance (1558) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139)

Published on in Vol 6, No 2 (2022): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40764, first published .
Analyzing Public Conversations About Heart Disease and Heart Health on Facebook From 2016 to 2021: Retrospective Observational Study Applying Latent Dirichlet Allocation Topic Modeling

Analyzing Public Conversations About Heart Disease and Heart Health on Facebook From 2016 to 2021: Retrospective Observational Study Applying Latent Dirichlet Allocation Topic Modeling

Analyzing Public Conversations About Heart Disease and Heart Health on Facebook From 2016 to 2021: Retrospective Observational Study Applying Latent Dirichlet Allocation Topic Modeling

Authors of this article:

Haoning Xue1 Author Orcid Image ;   Jingwen Zhang1, 2 Author Orcid Image ;   Kenji Sagae3 Author Orcid Image ;   Brian Nishimine1 Author Orcid Image ;   Yoshimi Fukuoka4 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Barrera R, Poindexter K, Tucker C, Winkler M, Dashti H. Amplifying the lived experiences of parenteral nutrition consumers through the thematic analysis of social media posts. Nutrition in Clinical Practice 2024;39(4):850 View

Conference Proceedings

  1. Rodriguez R, Rhald Padilla J, Darrel Montefalcon M, Abisado M, Raga R. 2023 11th International Conference on Information and Education Technology (ICIET). The Post Behind Anonymity: A Thematic Discourse Analysis of Facebook Posts from Confession Pages in different Universities in the Philippines View