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Citing this Article

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Published on 10.05.16 in Vol 18, No 5 (2016): May

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

Works citing "The Voice of Chinese Health Consumers: A Text Mining Approach to Web-Based Physician Reviews"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.4430):

(note that this is only a small subset of citations)

  1. Islam M, Hasan M, Wang X, Germack H, Noor-E-Alam M. A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining. Healthcare 2018;6(2):54
    CrossRef
  2. Hong YA, Liang C, Radcliff TA, Wigfall LT, Street RL. What Do Patients Say About Doctors Online? A Systematic Review of Studies on Patient Online Reviews. Journal of Medical Internet Research 2019;21(4):e12521
    CrossRef
  3. Bidmon S, Elshiewy O, Terlutter R, Boztug Y. What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data. Journal of Medical Internet Research 2020;22(2):e13830
    CrossRef
  4. Liu Q, Liao K, Tsoi KK, Wei Z. Acceptance Prediction for Answers on Online Health-care Community. BMC Bioinformatics 2019;20(S18)
    CrossRef
  5. Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1
    CrossRef
  6. Shah AM, Yan X, Shah SAA, Mamirkulova G. Mining patient opinion to evaluate the service quality in healthcare: a deep-learning approach. Journal of Ambient Intelligence and Humanized Computing 2020;11(7):2925
    CrossRef
  7. Shah AM, Yan X, Tariq S, Khan S. Listening to the patient voice: using a sentic computing model to evaluate physicians’ healthcare service quality for strategic planning in hospitals. Quality & Quantity 2020;
    CrossRef
  8. Deng Q, Gao Y, Wang C, Zhang H. Detecting information requirements for crisis communication from social media data: An interactive topic modeling approach. International Journal of Disaster Risk Reduction 2020;50:101692
    CrossRef
  9. Rivas R, Montazeri N, Le NX, Hristidis V. Automatic Classification of Online Doctor Reviews: Evaluation of Text Classifier Algorithms. Journal of Medical Internet Research 2018;20(11):e11141
    CrossRef
  10. Lin Y, Hong YA, Henson BS, Stevenson RD, Hong S, Lyu T, Liang C. Assessing Patient Experience and Healthcare Quality of Dental Care Using Patient Online Reviews in the United States: Mixed Methods Study. Journal of Medical Internet Research 2020;22(7):e18652
    CrossRef
  11. Li J, Liu M, Li X, Liu X, Liu J. Developing Embedded Taxonomy and Mining Patients’ Interests From Web-Based Physician Reviews: Mixed-Methods Approach. Journal of Medical Internet Research 2018;20(8):e254
    CrossRef
  12. Yan M, Tan H, Jia L, Akram U. The Antecedents of Poor Doctor-Patient Relationship in Mobile Consultation: A Perspective from Computer-Mediated Communication. International Journal of Environmental Research and Public Health 2020;17(7):2579
    CrossRef
  13. Shah AM, Yan X, Khan S, Khurrum W, Khan QR. A multi-modal approach to predict the strength of doctor–patient relationships. Multimedia Tools and Applications 2020;
    CrossRef
  14. Tapi Nzali MD, Bringay S, Lavergne C, Mollevi C, Opitz T. What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer. JMIR Medical Informatics 2017;5(3):e23
    CrossRef
  15. He L, Han D, Zhou X, Qu Z. The Voice of Drug Consumers: Online Textual Review Analysis Using Structural Topic Model. International Journal of Environmental Research and Public Health 2020;17(10):3648
    CrossRef
  16. Zaman N, Goldberg DM, Abrahams AS, Essig RA. Facebook Hospital Reviews: Automated Service Quality Detection and Relationships with Patient Satisfaction. Decision Sciences 2020;
    CrossRef
  17. Lantzy S, Anderson D. Can Consumers Use Online Reviews to Avoid Unsuitable Doctors? Evidence From RateMDs.com and the Federation of State Medical Boards. Decision Sciences 2020;51(4):962
    CrossRef
  18. Han X, Qu J, Zhang T. Exploring the impact of review valence, disease risk, and trust on patient choice based on online physician reviews. Telematics and Informatics 2019;45:101276
    CrossRef
  19. Zhang W, Deng Z, Hong Z, Evans R, Ma J, Zhang H. Unhappy Patients Are Not Alike: Content Analysis of the Negative Comments from China's Good Doctor Website. Journal of Medical Internet Research 2018;20(1):e35
    CrossRef
  20. Hu J, Zhang X, Yang Y, Liu Y, Chen X. New doctors ranking system based on VIKOR method. International Transactions in Operational Research 2020;27(2):1236
    CrossRef
  21. , , , , . Healthcare at Your Fingertips: The Acceptance and Adoption of Mobile Medical Treatment Services among Chinese Users. International Journal of Environmental Research and Public Health 2020;17(18):6895
    CrossRef
  22. Button K, Spasić I, Playle R, Owen D, Lau M, Hannaway L, Jones S. Using routine referral data for patients with knee and hip pain to improve access to specialist care. BMC Musculoskeletal Disorders 2020;21(1)
    CrossRef
  23. Powell J, Atherton H, Williams V, Mazanderani F, Dudhwala F, Woolgar S, Boylan A, Fleming J, Kirkpatrick S, Martin A, van Velthoven M, de Iongh A, Findlay D, Locock L, Ziebland S. Using online patient feedback to improve NHS services: the INQUIRE multimethod study. Health Services and Delivery Research 2019;7(38):1
    CrossRef
  24. Cho I, Lee M, Kim Y. What are the main patient safety concerns of healthcare stakeholders: a mixed-method study of Web-based text. International Journal of Medical Informatics 2020;140:104162
    CrossRef
  25. Wang J, Chiu Y, Yu H, Hsu Y. Understanding a Nonlinear Causal Relationship Between Rewards and Physicians’ Contributions in Online Health Care Communities: Longitudinal Study. Journal of Medical Internet Research 2017;19(12):e427
    CrossRef
  26. , , , , . Quantitative Ratings and Narrative Comments on Swiss Physician Rating Websites: Frequency Analysis. Journal of Medical Internet Research 2019;21(7):e13816
    CrossRef
  27. Min K, Song S, Min J. Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation Analysis. Journal of Medical Internet Research 2020;22(8):e19222
    CrossRef
  28. Chen X, Faviez C, Schuck S, Lillo-Le-Louët A, Texier N, Dahamna B, Huot C, Foulquié P, Pereira S, Leroux V, Karapetiantz P, Guenegou-Arnoux A, Katsahian S, Bousquet C, Burgun A. Mining Patients' Narratives in Social Media for Pharmacovigilance: Adverse Effects and Misuse of Methylphenidate. Frontiers in Pharmacology 2018;9
    CrossRef
  29. Deng Z, Hong Z, Zhang W, Evans R, Chen Y. The Effect of Online Effort and Reputation of Physicians on Patients’ Choice: 3-Wave Data Analysis of China’s Good Doctor Website. Journal of Medical Internet Research 2019;21(3):e10170
    CrossRef
  30. Han X, Li B, Zhang T, Qu J. Factors Associated With the Actual Behavior and Intention of Rating Physicians on Physician Rating Websites: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(6):e14417
    CrossRef
  31. Hao H, Zhang K, Wang W, Gao G. A tale of two countries: International comparison of online doctor reviews between China and the United States. International Journal of Medical Informatics 2017;99:37
    CrossRef
  32. Luo A, Xin Z, Yuan Y, Wen T, Xie W, Zhong Z, Peng X, Ouyang W, Hu C, Liu F, Chen Y, He H. Multidimensional Feature Classification of the Health Information Needs of Patients With Hypertension in an Online Health Community Through Analysis of 1000 Patient Question Records: Observational Study. Journal of Medical Internet Research 2020;22(5):e17349
    CrossRef
  33. TOPLU S, CANGÜR . Text Mining Method in the Field of Health. Konuralp Tıp Dergisi 2020;:236
    CrossRef
  34. Liu J, Zhang W, Jiang X, Zhou Y. Data Mining of the Reviews from Online Private Doctors. Telemedicine and e-Health 2020;26(9):1157
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.4430):

  1. Shah AM, Yan X, Shah SJ, Khan S. Smart Health. 2018. Chapter 19:191
    CrossRef