Published on in Vol 17, No 4 (2015): April

Identifying Key Hospital Service Quality Factors in Online Health Communities

Identifying Key Hospital Service Quality Factors in Online Health Communities

Identifying Key Hospital Service Quality Factors in Online Health Communities

Authors of this article:

Yuchul Jung1 Author Orcid Image ;   Cinyoung Hur2 Author Orcid Image ;   Dain Jung3 Author Orcid Image ;   Minki Kim4 Author Orcid Image

Journals

  1. Shah A, Yan X, Shah S, 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 View
  2. Zaman N, Goldberg D, Abrahams A, Essig R. Facebook Hospital Reviews: Automated Service Quality Detection and Relationships with Patient Satisfaction. Decision Sciences 2021;52(6):1403 View
  3. Raghupathi V, Zhou Y, Raghupathi W. Exploring Big Data Analytic Approaches to Cancer Blog Text Analysis. International Journal of Healthcare Information Systems and Informatics 2019;14(4):1 View
  4. Ha E, Lee H. Projecting service quality: The effects of social media reviews on service perception. International Journal of Hospitality Management 2018;69:132 View
  5. Myneni S, Cobb N, Cohen T. In Pursuit of Theoretical Ground in Behavior Change Support Systems: Analysis of Peer-to-Peer Communication in a Health-Related Online Community. Journal of Medical Internet Research 2016;18(2):e28 View
  6. Ranard B, Werner R, Antanavicius T, Schwartz H, Smith R, Meisel Z, Asch D, Ungar L, Merchant R. Yelp Reviews Of Hospital Care Can Supplement And Inform Traditional Surveys Of The Patient Experience Of Care. Health Affairs 2016;35(4):697 View
  7. Jung Y, Hur C, Kim M. Sustainable Situation-Aware Recommendation Services with Collective Intelligence. Sustainability 2018;10(5):1632 View
  8. Cui L, Chan H, Zhou Y, Dai J, Lim J. Exploring critical factors of green business failure based on Grey-Decision Making Trial and Evaluation Laboratory (DEMATEL). Journal of Business Research 2019;98:450 View
  9. Shah A, 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 2021;55(1):173 View
  10. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  11. Shah A, Yan X, Shah S, Shah S, Mamirkulova G. Exploring the impact of online information signals in leveraging the economic returns of physicians. Journal of Biomedical Informatics 2019;98:103272 View
  12. Ibáñez R, Lupiañez-Villanueva F. Análisis de 51.996 opiniones online sobre profesionales sanitarios en una web comercial. Revista de Calidad Asistencial 2017;32(5):294 View
  13. Shah A, Yan X, Tariq S, Ali M. What patients like or dislike in physicians: Analyzing drivers of patient satisfaction and dissatisfaction using a digital topic modeling approach. Information Processing & Management 2021;58(3):102516 View
  14. Lee H, Lee M, Lee H, Cruz R. Mining service quality feedback from social media: A computational analytics method. Government Information Quarterly 2021;38(2):101571 View
  15. Masson Z, Parmentier G. Drivers and mechanisms for online communities performance: A systematic literature review. European Management Journal 2023;41(4):590 View
  16. 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
  17. Liu X, Zhou Y, Wang Z. Preference access of users' cancer risk perception using disease-specific online medical inquiry texts. Information Processing & Management 2022;59(1):102737 View
  18. Shah A, Muhammad W, Lee K, Naqvi R. Examining Different Factors in Web-Based Patients’ Decision-Making Process: Systematic Review on Digital Platforms for Clinical Decision Support System. International Journal of Environmental Research and Public Health 2021;18(21):11226 View
  19. Hao D, Zhang R, Bai K. An integrated approach for service quality evaluation of online health communities based on q-rung orthopair fuzzy linguistic aggregation operators. Journal of Intelligent & Fuzzy Systems 2022;42(3):1907 View
  20. A. Rahim A, Ibrahim M, Musa K, Chua S, Yaacob N. Assessing Patient-Perceived Hospital Service Quality and Sentiment in Malaysian Public Hospitals Using Machine Learning and Facebook Reviews. International Journal of Environmental Research and Public Health 2021;18(18):9912 View
  21. Rahim A, Ibrahim M, Musa K, Chua S, Yaacob N. Patient Satisfaction and Hospital Quality of Care Evaluation in Malaysia Using SERVQUAL and Facebook. Healthcare 2021;9(10):1369 View
  22. Rahim A, Ibrahim M, Chua S, Musa K. Hospital Facebook Reviews Analysis Using a Machine Learning Sentiment Analyzer and Quality Classifier. Healthcare 2021;9(12):1679 View
  23. Hua Y, Shujuan W, Fucheng W. Online health community—An empirical analysis based on grounded theory and entropy weight TOPSIS method to evaluate the service quality. DIGITAL HEALTH 2023;9 View
  24. Gkioka G, Bothos T, Magoutas B, Mentzas G. Data analytics methods to measure service quality: A systematic review. Intelligent Decision Technologies 2023;17(4):1007 View
  25. 隋 靖. Research on the Evaluation of Sales Service Quality of BYD Pure Electric Vehicles Based on Text Mining. E-Commerce Letters 2024;13(01):50 View
  26. Liu X, Zhou Y, Wang Z, Kumar A, Biswas B. Disease Topic Modeling of Users' Inquiry Texts: A Text Mining-Based PQDR-LDA Model for Analyzing the Online Medical Records. IEEE Transactions on Engineering Management 2024;71:6319 View

Books/Policy Documents

  1. Noteboom C, Abdel-Rahman M. Delivering Superior Health and Wellness Management with IoT and Analytics. View
  2. Alali H. Recent Advances in Mathematical and Statistical Methods. View
  3. Raghupathi V, Zhou Y, Raghupathi W. Research Anthology on Big Data Analytics, Architectures, and Applications. View
  4. Denecke K. Sentiment Analysis in the Medical Domain. View