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

Social Media for Diabetes (35) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1666) Infodemiology and Infoveillance (1369) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050)

Published on in Vol 1, No 2 (2016): Jul-Dec

Use of Social Media in the Diabetes Community: An Exploratory Analysis of Diabetes-Related Tweets

Use of Social Media in the Diabetes Community: An Exploratory Analysis of Diabetes-Related Tweets

Use of Social Media in the Diabetes Community: An Exploratory Analysis of Diabetes-Related Tweets

Authors of this article:

Yang Liu1 Author Orcid Image ;   Qiaozhu Mei1, 2 Author Orcid Image ;   David A Hanauer1, 3 Author Orcid Image ;   Kai Zheng1, 4 Author Orcid Image ;   Joyce M Lee5, 6 Author Orcid Image
Article Authors Cited by (28) Tweetations (22) Metrics

Journals

  1. Litchman M, Walker H, Ng A, Wawrzynski S, Oser S, Greenwood D, Gee P, Lackey M, Oser T. State of the Science: A Scoping Review and Gap Analysis of Diabetes Online Communities. Journal of Diabetes Science and Technology 2019;13(3):466 View
  2. Pérez-Pérez M, Pérez-Rodríguez G, Fdez-Riverola F, Lourenço A. Using Twitter to Understand the Human Bowel Disease Community: Exploratory Analysis of Key Topics. Journal of Medical Internet Research 2019;21(8):e12610 View
  3. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  4. White K, Gebremariam A, Lewis D, Nordgren W, Wedding J, Pasek J, Garrity A, Hirschfeld E, Lee J. Motivations for Participation in an Online Social Media Community for Diabetes. Journal of Diabetes Science and Technology 2018;12(3):712 View
  5. Fatehi F, Menon A, Bird D. Diabetes Care in the Digital Era: a Synoptic Overview. Current Diabetes Reports 2018;18(7) View
  6. Zaccardi F, Davies M, Khunti K. The present and future scope of real‐world evidence research in diabetes: What questions can and cannot be answered and what might be possible in the future?. Diabetes, Obesity and Metabolism 2020;22(S3):21 View
  7. Wake D. The future of diabetes education. Practical Diabetes 2019;36(6):196 View
  8. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  9. Oser T, Oser S, McGinley E, Stuckey H. A Novel Approach to Identifying Barriers and Facilitators in Raising a Child With Type 1 Diabetes: Qualitative Analysis of Caregiver Blogs. JMIR Diabetes 2017;2(2):e27 View
  10. Wakamiya S, Matsune S, Okubo K, Aramaki E. Causal Relationships Among Pollen Counts, Tweet Numbers, and Patient Numbers for Seasonal Allergic Rhinitis Surveillance: Retrospective Analysis. Journal of Medical Internet Research 2019;21(2):e10450 View
  11. Talbot C, O'Dwyer S, Clare L, Heaton J, Anderson J. How people with dementia use twitter: A qualitative analysis. Computers in Human Behavior 2020;102:112 View
  12. deBronkart D. Open Access as a Revolution: Knowledge Alters Power. Journal of Medical Internet Research 2019;21(12):e16368 View
  13. Patel K, Zainab K, Heppner A, Srivastava G, Mago V. Using Twitter for diabetes community analysis. Network Modeling Analysis in Health Informatics and Bioinformatics 2020;9(1) View
  14. Myneni S, Lewis B, Singh T, Paiva K, Kim S, Cebula A, Villanueva G, Wang J. Diabetes Self-Management in the Age of Social Media: Large-Scale Analysis of Peer Interactions Using Semiautomated Methods. JMIR Medical Informatics 2020;8(6):e18441 View
  15. Chalmers K, Smith M, Moreno M, Malik F. “It Got Likes, But I Don’t Think People Understood”: A Qualitative Study of Adolescent Experiences Discussing Type 1 Diabetes on Social Media. Journal of Diabetes Science and Technology 2022;16(4):858 View
  16. Pérez-Aldana C, Lewinski A, Johnson C, Vorderstrasse A, Myneni S. Exchanges in a Virtual Environment for Diabetes Self-Management Education and Support: Social Network Analysis. JMIR Diabetes 2021;6(1):e21611 View
  17. Ríssola E, Losada D, Crestani F. A Survey of Computational Methods for Online Mental State Assessment on Social Media. ACM Transactions on Computing for Healthcare 2021;2(2):1 View
  18. Shaw G, Zimmerman M, Vasquez-Huot L, Karami A. Deciphering Latent Health Information in Social Media Using a Mixed-Methods Design. Healthcare 2022;10(11):2320 View
  19. Pirim H, Nagahi M, Larif O, Nagahisarchoghaei M, Jaradat R. Integrated twitter analysis to distinguish systems thinkers at various levels: a case study of COVID-19. Applied Network Science 2023;8(1) View
  20. Bedford-Petersen C, Weston S. Mapping Individual Differences on the Internet: Case Study of the Type 1 Diabetes Community. JMIR Diabetes 2021;6(4):e30756 View
  21. Ahne A, Khetan V, Tannier X, Rizvi M, Czernichow T, Orchard F, Bour C, Fano A, Fagherazzi G. Extraction of Explicit and Implicit Cause-Effect Relationships in Patient-Reported Diabetes-Related Tweets From 2017 to 2021: Deep Learning Approach. JMIR Medical Informatics 2022;10(7):e37201 View
  22. Ramamoorthy T, Kulothungan V, Mappillairaju B. Topic modeling and social network analysis approach to explore diabetes discourse on Twitter in India. Frontiers in Artificial Intelligence 2024;7 View
  23. Sousa‐Pinto B, Jankin S, Vieira R, Marques‐Cruz M, Fonseca J, Bousquet J. English tweets on allergy: Content analysis and association with surveillance data. Clinical & Experimental Allergy 2024;54(7):500 View
  24. Roudani M, Elkari B, El Moutaouakil K, Ourabah L, Hicham B, Chellak S. Twitter-sentiment analysis of Moroccan diabetic using Fuzzy C-means SMOTE and deep neural network. Mathematical Modeling and Computing 2024;11(3):835 View