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Journal of Medical Internet Research

Citing this Article

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Published on 01.11.13 in Vol 15, No 11 (2013): November

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

Works citing "Use of Sentiment Analysis for Capturing Patient Experience From Free-Text Comments Posted Online"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2721):

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

  1. 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
  2. Xu Z, Guo H. Using Text Mining to Compare Online Pro- and Anti-Vaccine Headlines: Word Usage, Sentiments, and Online Popularity. Communication Studies 2018;69(1):103
    CrossRef
  3. Wang X, Parameswaran S, Bagul DM, Kishore R. Can online social support be detrimental in stigmatized chronic diseases? A quadratic model of the effects of informational and emotional support on self-care behavior of HIV patients. Journal of the American Medical Informatics Association 2018;
    CrossRef
  4. Emmert M, Meszmer N, Schlesinger M. A cross-sectional study assessing the association between online ratings and clinical quality of care measures for US hospitals: results from an observational study. BMC Health Services Research 2018;18(1)
    CrossRef
  5. Lu Y, Wu Y, Liu J, Li J, Zhang P. Understanding Health Care Social Media Use From Different Stakeholder Perspectives: A Content Analysis of an Online Health Community. Journal of Medical Internet Research 2017;19(4):e109
    CrossRef
  6. Metwally O, Blumberg S, Ladabaum U, Sinha SR. Using Social Media to Characterize Public Sentiment Toward Medical Interventions Commonly Used for Cancer Screening: An Observational Study. Journal of Medical Internet Research 2017;19(6):e200
    CrossRef
  7. Kim S, Oh J. Information science techniques for investigating research areas: a case study in telecommunications policy. The Journal of Supercomputing 2017;
    CrossRef
  8. Piryani R, Madhavi D, Singh V. Analytical mapping of opinion mining and sentiment analysis research during 2000–2015. Information Processing & Management 2017;53(1):122
    CrossRef
  9. Farrington C, Stewart ZA, Barnard K, Hovorka R, Murphy HR. Experiences of closed-loop insulin delivery among pregnant women with Type 1 diabetes. Diabetic Medicine 2017;34(10):1461
    CrossRef
  10. MacLaren R, Tran VH, Chiappe D. Effects of motivation orientation on schoolwork enjoyment and achievement and study habits. Thinking Skills and Creativity 2017;24:199
    CrossRef
  11. Tang C, Zhou L, Plasek J, Rozenblum R, Bates D. Comment Topic Evolution on a Cancer Institution’s Facebook Page. Applied Clinical Informatics 2017;08(03):854
    CrossRef
  12. Matthies B, Coners A. Document Selection for Knowledge Discovery in Texts: Framework Development and Demonstration. Journal of Information & Knowledge Management 2017;16(04):1750038
    CrossRef
  13. Gibbons C, Richards S, Valderas JM, Campbell J. Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy. Journal of Medical Internet Research 2017;19(3):e65
    CrossRef
  14. Tanniru M, Khuntia J. Dimensions of Patient Experience and Overall Satisfaction in Emergency Departments. Journal of Patient Experience 2017;4(3):95
    CrossRef
  15. Choi S, Lee J, Kang M, Min H, Chang Y, Yoon S. Large-scale machine learning of media outlets for understanding public reactions to nation-wide viral infection outbreaks. Methods 2017;129:50
    CrossRef
  16. Urquhart C, Tbaishat D. Reflections on the value and impact of library and information services. Performance Measurement and Metrics 2016;17(1):29
    CrossRef
  17. Hao H, Zhang K. The Voice of Chinese Health Consumers: A Text Mining Approach to Web-Based Physician Reviews. Journal of Medical Internet Research 2016;18(5):e108
    CrossRef
  18. Wagland R, Recio-Saucedo A, Simon M, Bracher M, Hunt K, Foster C, Downing A, Glaser A, Corner J. Development and testing of a text-mining approach to analyse patients’ comments on their experiences of colorectal cancer care. BMJ Quality & Safety 2016;25(8):604
    CrossRef
  19. Mazzocut M, Truccolo I, Antonini M, Rinaldi F, Omero P, Ferrarin E, De Paoli P, Tasso C. Web Conversations About Complementary and Alternative Medicines and Cancer: Content and Sentiment Analysis. Journal of Medical Internet Research 2016;18(6):e120
    CrossRef
  20. Taylor CA, Al-Hiyari R, Lee SJ, Priebe A, Guerrero LW, Bales A. Beliefs and ideologies linked with approval of corporal punishment: a content analysis of online comments. Health Education Research 2016;31(4):563
    CrossRef
  21. Patel S, Cain R, Neailey K, Hooberman L. Exploring Patients’ Views Toward Giving Web-Based Feedback and Ratings to General Practitioners in England: A Qualitative Descriptive Study. Journal of Medical Internet Research 2016;18(8):e217
    CrossRef
  22. McCoy TH, Castro VM, Cagan A, Roberson AM, Kohane IS, Perlis RH, Ramagopalan SV. Sentiment Measured in Hospital Discharge Notes Is Associated with Readmission and Mortality Risk: An Electronic Health Record Study. PLOS ONE 2015;10(8):e0136341
    CrossRef
  23. Maramba ID, Davey A, Elliott MN, Roberts M, Roland M, Brown F, Burt J, Boiko O, Campbell J. Web-Based Textual Analysis of Free-Text Patient Experience Comments From a Survey in Primary Care. JMIR Medical Informatics 2015;3(2):e20
    CrossRef
  24. Li M, Xiang Y, Zhang B, Huang Z. A Sentiment Delivering Estimate Scheme Based on Trust Chain in Mobile Social Network. Mobile Information Systems 2015;2015:1
    CrossRef
  25. Jung Y, Hur C, Jung D, Kim M. Identifying Key Hospital Service Quality Factors in Online Health Communities. Journal of Medical Internet Research 2015;17(4):e90
    CrossRef
  26. Patel S, Cain R, Neailey K, Hooberman L. General Practitioners’ Concerns About Online Patient Feedback: Findings From a Descriptive Exploratory Qualitative Study in England. Journal of Medical Internet Research 2015;17(12):e276
    CrossRef
  27. Schlesinger M, Grob R, Shaller D. Using Patient-Reported Information to Improve Clinical Practice. Health Services Research 2015;50:2116
    CrossRef
  28. Alemi F. Foreward to special issue on health analytics. Health Care Management Science 2015;18(1):1
    CrossRef
  29. Rastegar-Mojarad M, Ye Z, Wall D, Murali N, Lin S. Collecting and Analyzing Patient Experiences of Health Care From Social Media. JMIR Research Protocols 2015;4(3):e78
    CrossRef
  30. Emmert M, Meier F, Heider A, Dürr C, Sander U. What do patients say about their physicians? An analysis of 3000 narrative comments posted on a German physician rating website. Health Policy 2014;118(1):66
    CrossRef
  31. Ozan-Rafferty ME, Johnson JA, Shah GH, Kursun A. In the Words of the Medical Tourist: An Analysis of Internet Narratives by Health Travelers to Turkey. Journal of Medical Internet Research 2014;16(2):e43
    CrossRef
  32. Greaves F, Millett C, Nuki P. England’s Experience Incorporating “Anecdotal” Reports From Consumers into Their National Reporting System. Medical Care Research and Review 2014;71(5_suppl):65S
    CrossRef
  33. Kim M, Jung Y, Jung D, Hur C. Investigating the Congruence of Crowdsourced Information With Official Government Data: The Case of Pediatric Clinics. Journal of Medical Internet Research 2014;16(2):e29
    CrossRef
  34. Verhoef LM, Van de Belt TH, Engelen LJ, Schoonhoven L, Kool RB. Social Media and Rating Sites as Tools to Understanding Quality of Care: A Scoping Review. Journal of Medical Internet Research 2014;16(2):e56
    CrossRef
  35. Wallace BC, Paul MJ, Sarkar U, Trikalinos TA, Dredze M. A large-scale quantitative analysis of latent factors and sentiment in online doctor reviews. Journal of the American Medical Informatics Association 2014;21(6):1098
    CrossRef
  36. Greaves F, Laverty AA, Cano DR, Moilanen K, Pulman S, Darzi A, Millett C. Tweets about hospital quality: a mixed methods study. BMJ Quality & Safety 2014;23(10):838
    CrossRef
  37. Rafferty MO, Grey K. Beyond Patient Experience Surveys: Leveraging Social Media to Glean Patient Feedback. Nurse Leader 2014;12(3):31
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.2721)

:
  1. Luna-Aveiga H, Medina-Moreira J, Lagos-Ortiz K, Apolinario O, Paredes-Valverde MA, del Pilar Salas-Zárate M, Valencia-García R. Advanced Computational Methods for Knowledge Engineering. 2018. Chapter 13:141
    CrossRef
  2. Bernabé-Moreno J, Tejeda-Lorente A, Porcel C, Herrera-Viedma E. Advances in Fuzzy Logic and Technology 2017. 2018. Chapter 19:199
    CrossRef
  3. Lamprinakos G, Aristeidopoulou IA, Asanin S, Kapsalis AP, Anadiotis AG, Kaklamani DI, Venieris IS. Encyclopedia of E-Health and Telemedicine. 2016. chapter 68:889
    CrossRef