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

Peer-to-Peer Support and Online Communities (803) Innovations and Technology for Healthy Eating Education (491) Innovations and Technology for Physical Activity Education (936) Machine Learning (2095) Natural Language Processing (923)

Published on in Vol 22, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13745, first published .
Understanding Weight Loss via Online Discussions: Content Analysis of Reddit Posts Using Topic Modeling and Word Clustering Techniques

Understanding Weight Loss via Online Discussions: Content Analysis of Reddit Posts Using Topic Modeling and Word Clustering Techniques

Understanding Weight Loss via Online Discussions: Content Analysis of Reddit Posts Using Topic Modeling and Word Clustering Techniques

Authors of this article:

Yang Liu1 Author Orcid Image ;   Zhijun Yin2, 3 Author Orcid Image
Article Authors Cited by (25) Tweetations (4) Metrics

Journals

  1. Yin Z, Song L, Clayton E, Malin B, MacLure K. Health and kinship matter: Learning about direct-to-consumer genetic testing user experiences via online discussions. PLOS ONE 2020;15(9):e0238644 View
  2. Singh T, Roberts K, Cohen T, Cobb N, Wang J, Fujimoto K, Myneni S. Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review. JMIR Public Health and Surveillance 2020;6(4):e21660 View
  3. Zowalla R, Pfeifer D, Wetter T, Al-Yateem N. Readability and topics of the German Health Web: Exploratory study and text analysis. PLOS ONE 2023;18(2):e0281582 View
  4. Tripathi S, Parker P, Prabhu A, Thomas K, Rodriguez A. An Examination of Patients and Caregivers on Reddit Navigating Brain Cancer: Content Analysis of the Brain Tumor Subreddit. JMIR Cancer 2022;8(2):e35324 View
  5. Pollack C, Emond J, O'Malley A, Byrd A, Green P, Miller K, Vosoughi S, Gilbert-Diamond D, Onega T. Characterizing the Prevalence of Obesity Misinformation, Factual Content, Stigma, and Positivity on the Social Media Platform Reddit Between 2011 and 2019: Infodemiology Study. Journal of Medical Internet Research 2022;24(12):e36729 View
  6. Nagpal M, Barbaric A, Sherifali D, Morita P, Cafazzo J. Patient-Generated Data Analytics of Health Behaviors of People Living With Type 2 Diabetes: Scoping Review. JMIR Diabetes 2021;6(4):e29027 View
  7. Côté M, Lamarche B. Artificial intelligence in nutrition research: perspectives on current and future applications. Applied Physiology, Nutrition, and Metabolism 2022;47(1):1 View
  8. Liu Y, Yin Z, Wan Z, Yan C, Xia W, Ni C, Clayton E, Vorobeychik Y, Kantarcioglu M, Malin B. Implicit Incentives Among Reddit Users to Prioritize Attention Over Privacy and Reveal Their Faces When Discussing Direct-to-Consumer Genetic Test Results: Topic and Attention Analysis. JMIR Infodemiology 2022;2(2):e35702 View
  9. Yom Tov E, Hochberg I. A Large-Scale Observational Analysis of Social Media Data Reveals Major Public Misperception of the Attainability of Drastic Weight Loss by Dieting. Obesity Facts 2023;16(2):141 View
  10. Yang Q, Ledbetter A, Zhuang J, Richards A. Theme and sentiment of posts in a weight loss subreddit predict popularity, engagement, and users’ weight loss: a computational approach. Human Communication Research 2023;49(4):452 View
  11. Naroji S, John J, Gomez-Lobo V. Understanding PCOS-Related Content across Social Media Platforms—A Cross-Sectional Analysis. Journal of Pediatric and Adolescent Gynecology 2024;37(2):142 View
  12. Nagpal M, Sherifali D, Morita P, Cafazzo J. Managing Type 2 Diabetes during the COVID-19 Pandemic: Comparison Between Systematic Literature Review and Social Media Data (Preprint). Interactive Journal of Medical Research 2023 View
  13. Meacham M, Nobles A, Bone C, Gilbert M, Thrul J, Mitra S. The Reddit cannabis subjective highness rating scale: Applying computational social science to explore psychological and environmental correlates of naturalistic cannabis use. PLOS ONE 2024;19(6):e0300290 View
  14. Yang F, Pham B, Zhang S, Kriss L. Talking about pain plainly: authentic expression of pain management on Reddit. Health & New Media Research 2024;8(1):73 View
  15. Nagpal M, Jalali N, Sherifali D, Morita P, Cafazzo J. Managing Type 2 Diabetes during the COVID-19 Pandemic: An Investigation of Reddit Data using LDA Topic Modelling and VADER sEntiment Analysis (Preprint). JMIR Formative Research 2023 View
  16. Chan G, Fung M, Warrington J, Nowak S. Understanding Health-Related Discussions on Reddit: Development of a Topic Assignment Method and Exploratory Analysis. JMIR Formative Research 2025;9:e55309 View
  17. Jin C, Zhu Z. Multimorbidity patterns and early signals of diabetes in online communities. JAMIA Open 2025;8(3) View
  18. Shah M, Acaf Y, Mackert M. Understanding conversations on alcohol across diverse Reddit communities: a computational analysis. Journal of Computational Social Science 2025;8(4) View
  19. Sorrell-Medina Z, Tessler T, Chung E. Expanding Citizenry Exclusion: The Case of Asian American Exclusion During COVID-19. Race and Social Problems 2025;17(4):509 View
  20. Betz C, Al Masri M, König L, Bartelmeß T. Identifying Social Media‐Based Interactions That Help Adults to Adhere to Weight Loss Goals: A Systematic Review. Obesity Reviews 2025 View
  21. Cho H, Cauble C. Digital narratives on workplace bullying and the role of human resource development: topic modelling and sentiment analysis. International Journal of Organizational Analysis 2025:1 View

Books/Policy Documents

  1. Gamage D, Chen J, Ghasiya P, Sasahara K. Frontiers in Fake Media Generation and Detection. View
  2. Côté M, Lamarche B. Artificial Intelligence in Clinical Practice. View

Conference Proceedings

  1. Gamage D, Ghasiya P, Bonagiri V, Whiting M, Sasahara K. CHI Conference on Human Factors in Computing Systems. Are Deepfakes Concerning? Analyzing Conversations of Deepfakes on Reddit and Exploring Societal Implications View
  2. Batool V, Murnane E. Scrutinizing Empathy-Centric Design Beyond the Individual. Weight Bias in Design: Unpacking Implicit Researcher Beliefs for Building Empathy View