Published on in Vol 8, No 5 (2020): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17813, first published .
Determining the Topic Evolution and Sentiment Polarity for Albinism in a Chinese Online Health Community: Machine Learning and Social Network Analysis

Determining the Topic Evolution and Sentiment Polarity for Albinism in a Chinese Online Health Community: Machine Learning and Social Network Analysis

Determining the Topic Evolution and Sentiment Polarity for Albinism in a Chinese Online Health Community: Machine Learning and Social Network Analysis

Journals

  1. Shen L, Yao R, Zhang W, Evans R, Cao G, Zhang Z. Emotional Attitudes of Chinese Citizens on Social Distancing During the COVID-19 Outbreak: Analysis of Social Media Data. JMIR Medical Informatics 2021;9(3):e27079 View
  2. Miller E, Woodward A, Flinchum G, Young J, Tabor H, Halley M. Opportunities and pitfalls of social media research in rare genetic diseases: a systematic review. Genetics in Medicine 2021 View
  3. Yao Z, Ni Z, Zhang B, Du J. Do Informational and Emotional Elements Differ between Online Psychological and Physiological Disease Communities in China? A Comparative Study of Depression and Diabetes. International Journal of Environmental Research and Public Health 2022;19(4):2167 View
  4. Bukar U, Sidi F, Jabar M, Nor R, Abdullah S, Ishak I, Alabadla M, Alkhalifah A. How Advanced Technological Approaches Are Reshaping Sustainable Social Media Crisis Management and Communication: A Systematic Review. Sustainability 2022;14(10):5854 View
  5. Shuai M, He D, Chen X. Optimizing weighted gene co-expression network analysis with a multi-threaded calculation of the topological overlap matrix. Statistical Applications in Genetics and Molecular Biology 2021;20(4-6):145 View
  6. Wu J, Chien T, Tsai Y, Wang H, Kan W, Wang L. Using the forest plot to compare citation achievements in bibliographic and meta-analysis studies since 2011 using data on PubMed Central: A retrospective study. Medicine 2022;101(27):e29213 View
  7. Qin M, Zhu W, You C, Li S, Qiu S. Patient's behavior of selection physician in online health communities: Based on an Elaboration likelihood model. Frontiers in Public Health 2022;10 View
  8. Guo S, Dang Y, She B, Li Y. Sharing intention of electronic health records in online health communities: Patients’ behavioral decisions in the context of privacy protection measures. Frontiers in Psychology 2022;13 View
  9. Lei Y, Xu S, Zhou L. User Behaviors and User-Generated Content in Chinese Online Health Communities: Comparative Study. Journal of Medical Internet Research 2021;23(12):e19183 View
  10. Zhang W, Yao R, Evans R, Huang W, Cao G, Shen L. Collaboration of issuing agencies and topic evolution of health informatisation policies in China. Journal of Information Science 2023;49(6):1692 View
  11. Shi J, Khoo Z. Online health community for change: Analysis of self-disclosure and social networks of users with depression. Frontiers in Psychology 2023;14 View
  12. Lu Y, Wang X, Su L, Zhao H. Multiplex Social Network Analysis to Understand the Social Engagement of Patients in Online Health Communities. Mathematics 2023;11(21):4412 View
  13. Yuan W, Qin H, Bi H, Zhao D, Zhang Y, Chen W. Ssc-mir-221-3p regulates melanin production in Xiang pigs melanocytes by targeting the TYRP1 gene. BMC Genomics 2023;24(1) View
  14. Nie L, Xu J, Wang R, Tilga H. Health information needs and feedback of users in the online TCM community. PLOS ONE 2024;19(3):e0301536 View
  15. Zhao Y, Zhang L. Getting better? Examining the effects of social support in OHCs on users’ emotional improvement. Information Processing & Management 2024;61(4):103754 View
  16. Xi N, Ji H, Wang L. Understanding Sarcoidosis Using Large Language Models and Social Media Data. Journal of Healthcare Informatics Research 2024 View

Books/Policy Documents

  1. Viloria A, Parra K, Conde M, Lezama O. Information, Communication and Computing Technology. View