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

Behavioural Surveillance for Public Health (294) Infodemiology and Infoveillance (1563) Insomnia and Sleep Hygiene (248) Innovative Methods in Public Health and Surveillance (385) Public (e)Health, Digital Epidemiology and Public Health Informatics (1019) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1142) Natural Language Processing (921) Machine Learning (2088) Crowdsourcing and Mechanical Turks (103)

Published on in Vol 8, No 2 (2022): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32355, first published .
Physical Activity, Sedentary Behavior, and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research

Physical Activity, Sedentary Behavior, and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research

Physical Activity, Sedentary Behavior, and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research

Authors of this article:

Zahra Shakeri Hossein Abad1, 2 Author Orcid Image ;   Gregory P Butler3 Author Orcid Image ;   Wendy Thompson3 Author Orcid Image ;   Joon Lee2, 4, 5 Author Orcid Image
Article Authors Cited by (3) Tweetations (15) Metrics

Journals

  1. Shakeri Hossein Abad Z, Butler G, Thompson W, Lee J. Crowdsourcing for Machine Learning in Public Health Surveillance: Lessons Learned From Amazon Mechanical Turk. Journal of Medical Internet Research 2022;24(1):e28749 View
  2. Petit P, Vuillerme N. Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024). JMIR Public Health and Surveillance 2025;11:e62939 View

Conference Proceedings

  1. Kazari K, Chen Y, Shakeri Z. 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy View