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

Innovations and Technology for Healthy Eating Education (414) Machine Learning (1465)

Published on in Vol 22, No 3 (2020): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15700, first published .
Exploring Abnormal Behavior Patterns of Online Users With Emotional Eating Behavior: Topic Modeling Study

Exploring Abnormal Behavior Patterns of Online Users With Emotional Eating Behavior: Topic Modeling Study

Exploring Abnormal Behavior Patterns of Online Users With Emotional Eating Behavior: Topic Modeling Study

Authors of this article:

Youjin Hwang1 Author Orcid Image ;   Hyung Jun Kim1 Author Orcid Image ;   Hyung Jin Choi2 Author Orcid Image ;   Joonhwan Lee1 Author Orcid Image
Article Authors Cited by (24) Tweetations (3) Metrics

Journals

  1. Petersen C, Halter R, Kotz D, Loeb L, Cook S, Pidgeon D, Christensen B, Batsis J. Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study. JMIR mHealth and uHealth 2020;8(8):e16862 View
  2. Chandrasekaran R, Mehta V, Valkunde T, Moustakas E. Topics, Trends, and Sentiments of Tweets About the COVID-19 Pandemic: Temporal Infoveillance Study. Journal of Medical Internet Research 2020;22(10):e22624 View
  3. Wang S. Machine learning to advance the prediction, prevention and treatment of eating disorders. European Eating Disorders Review 2021;29(5):683 View
  4. Opitz M, Newman E, Sharpe H. Understanding perceived characteristics and causes of orthorexia nervosa in online communities—A Reddit analysis. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2022;16(5) View
  5. Hagg L, Merkouris S, O’Dea G, Francis L, Greenwood C, Fuller-Tyszkiewicz M, Westrupp E, Macdonald J, Youssef G. Examining Analytic Practices in Latent Dirichlet Allocation Within Psychological Science: Scoping Review. Journal of Medical Internet Research 2022;24(11):e33166 View
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  8. Parola A, Lin J, Simonsen A, Bliksted V, Zhou Y, Wang H, Inoue L, Koelkebeck K, Fusaroli R. Speech disturbances in schizophrenia: Assessing cross-linguistic generalizability of NLP automated measures of coherence. Schizophrenia Research 2023;259:59 View
  9. Almenara C, Baccini A. 40 years of research on eating disorders in domain-specific journals: Bibliometrics, network analysis, and topic modeling. PLOS ONE 2022;17(12):e0278981 View
  10. 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
  11. Zhang T, Schoene A, Ji S, Ananiadou S. Natural language processing applied to mental illness detection: a narrative review. npj Digital Medicine 2022;5(1) View
  12. Gao H, Lu S, Kou X. Research on the identification of medical service quality factors: based on a data-driven method. Internet Research 2022;32(5):1617 View
  13. Smith E, Michalski S, Knauth K, Kaspar K, Reiter N, Peters J. Large-Scale Web Scraping for Problem Gambling Research: A Case Study of COVID-19 Lockdown Effects in Germany. Journal of Gambling Studies 2023;39(3):1487 View
  14. Fardouly J, Crosby R, Sukunesan S. Potential benefits and limitations of machine learning in the field of eating disorders: current research and future directions. Journal of Eating Disorders 2022;10(1) View
  15. Laureate C, Buntine W, Linger H. A systematic review of the use of topic models for short text social media analysis. Artificial Intelligence Review 2023;56(12):14223 View
  16. Ghaffari M, Aliahmadi A, Khalkhali A, Zakery A, Daim T, Yalcin H. Topic-based technology mapping using patent data analysis: A case study of vehicle tires. Technological Forecasting and Social Change 2023;193:122576 View
  17. Miao W, Lin K, Wu C, Sun J, Sun W, Wei W, Gu C. How Could Consumers’ Online Review Help Improve Product Design Strategy?. Information 2023;14(8):434 View
  18. de Barcellos M, Perin M, Lähteenmäki L, Grunert K. Beyond “belly hunger”: Capabilities and motivation for eating nutritionally recommended food during stressful times. Science Talks 2024;10:100337 View
  19. Merhbene G, Puttick A, Kurpicz-Briki M. Investigating machine learning and natural language processing techniques applied for detecting eating disorders: a systematic literature review. Frontiers in Psychiatry 2024;15 View
  20. Ghosh S, Burger P, Simeunovic-Ostojic M, Maas J, Petković M. Review of machine learning solutions for eating disorders. International Journal of Medical Informatics 2024;189:105526 View
  21. Flauzino P, Bezerra I. Comportamento alimentar em mulheres negras puérperas com obesidade. Gestão & Cuidado em Saúde 2024:e12204 View

Books/Policy Documents

  1. Mena A, Reátegui R. Applied Technologies. View
  2. Côté M, Lamarche B. Artificial Intelligence in Clinical Practice. View