Published on 01.11.13 in Vol 15, No 11 (2013): November
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)
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Xu J, Huang F, Zhang X, Wang S, Li C, Li Z, He Y. Sentiment analysis of social images via hierarchical deep fusion of content and links. Applied Soft Computing 2019;80:387
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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
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Schlesinger M, Grob R, Shaller D. Using Patient‐Reported Information to Improve Clinical Practice. Health Services Research 2015;50(S2):2116
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Contreras I, Vehi J. Artificial Intelligence for Diabetes Management and Decision Support: Literature Review. Journal of Medical Internet Research 2018;20(5):e10775
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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
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Sanders C, Nahar P, Small N, Hodgson D, Ong BN, Dehghan A, Sharp CA, Dixon WG, Lewis S, Kontopantelis E, Daker-White G, Bower P, Davies L, Kayesh H, Spencer R, McAvoy A, Boaden R, Lovell K, Ainsworth J, Nowakowska M, Shepherd A, Cahoon P, Hopkins R, Allen D, Lewis A, Nenadic G. Digital methods to enhance the usefulness of patient experience data in services for long-term conditions: the DEPEND mixed-methods study. Health Services and Delivery Research 2020;8(28):1
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. The Content and Nature of Narrative Comments on Swiss Physician Rating Websites: Analysis of 849 Comments. Journal of Medical Internet Research 2019;21(9):e14336
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Gordon D, Ford A, Triedman N, Hart K, Perlis R. Health Care Consumer Shopping Behaviors and Sentiment: Qualitative Study. Journal of Participatory Medicine 2020;12(2):e13924
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Sedrak MS, Salgia MM, Decat Bergerot C, Ashing-Giwa K, Cotta BN, Adashek JJ, Dizman N, Wong AR, Pal SK, Bergerot PG. Examining Public Communication About Kidney Cancer on Twitter. JCO Clinical Cancer Informatics 2019;(3):1
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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
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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
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Park SH, Hong SH. Identification of Primary Medication Concerns Regarding Thyroid Hormone Replacement Therapy From Online Patient Medication Reviews: Text Mining of Social Network Data. Journal of Medical Internet Research 2018;20(10):e11085
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Mujtaba G, Shuib L, Idris N, Hoo WL, Raj RG, Khowaja K, Shaikh K, Nweke HF. Clinical text classification research trends: Systematic literature review and open issues. Expert Systems with Applications 2019;116:494
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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 2021;55(1):173
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Subirats L, Reguera N, Bañón A, Gómez-Zúñiga B, Minguillón J, Armayones M. Mining Facebook Data of People with Rare Diseases: A Content-Based and Temporal Analysis. International Journal of Environmental Research and Public Health 2018;15(9):1877
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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
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Menendez ME, Shaker J, Lawler SM, Ring D, Jawa A. Negative Patient-Experience Comments After Total Shoulder Arthroplasty. Journal of Bone and Joint Surgery 2019;101(4):330
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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
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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
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Tanniru M, Khuntia J. Dimensions of Patient Experience and Overall Satisfaction in Emergency Departments. Journal of Patient Experience 2017;4(3):95
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Kaur W, Balakrishnan V, Rana O, Sinniah A. Liking, sharing, commenting and reacting on Facebook: User behaviors’ impact on sentiment intensity. Telematics and Informatics 2019;39:25
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Zunic A, Corcoran P, Spasic I. Sentiment Analysis in Health and Well-Being: Systematic Review. JMIR Medical Informatics 2020;8(1):e16023
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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
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Tsoi KK, Chan NB, Yiu KK, Poon SK, Lin B, Ho K. Machine Learning Clustering for Blood Pressure Variability Applied to Systolic Blood Pressure Intervention Trial (SPRINT) and the Hong Kong Community Cohort. Hypertension 2020;76(2):569
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. Increasing the Impact of JMIR Journals in the Attention Economy. Journal of Medical Internet Research 2019;21(10):e16172
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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
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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
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Hart KL, Perlis RH, McCoy TH. What do patients learn about psychotropic medications on the web? A natural language processing study. Journal of Affective Disorders 2020;260:366
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Rafferty MO, Grey K. Beyond Patient Experience Surveys: Leveraging Social Media to Glean Patient Feedback. Nurse Leader 2014;12(3):31
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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
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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
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Kim S, Oh J. Information science techniques for investigating research areas: a case study in telecommunications policy. The Journal of Supercomputing 2018;74(12):6691
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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
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Hu G, Han X, Zhou H, Liu Y. Public Perception on Healthcare Services: Evidence from Social Media Platforms in China. International Journal of Environmental Research and Public Health 2019;16(7):1273
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Czyżewski A, Hoffmann P, Szczuko P, Kurowski A, Lech M, Szczodrak M. Analysis of results of large‐scale multimodal biometric identity verification experiment. IET Biometrics 2019;8(1):92
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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)
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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
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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
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Matthies B, Coners A. Document Selection for Knowledge Discovery in Texts: Framework Development and Demonstration. Journal of Information & Knowledge Management 2017;16(04):1750038
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Boylan A, Williams V, Powell J. Online patient feedback: a scoping review and stakeholder consultation to guide health policy. Journal of Health Services Research & Policy 2020;25(2):122
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Zaman N, Goldberg DM, Abrahams AS, Essig RA. Facebook Hospital Reviews: Automated Service Quality Detection and Relationships with Patient Satisfaction. Decision Sciences 2021;52(6):1403
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Abraham TH, Deen TL, Hamilton M, True G, O’Neil MT, Blanchard J, Uddo M. Analyzing free-text survey responses: An accessible strategy for developing patient-centered programs and program evaluation. Evaluation and Program Planning 2020;78:101733
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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
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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;25(8):931
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Chen D, Zhang R, Feng J, Liu K. Fulfilling information needs of patients in online health communities. Health Information & Libraries Journal 2020;37(1):48
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Gohil S, Vuik S, Darzi A. Sentiment Analysis of Health Care Tweets: Review of the Methods Used. JMIR Public Health and Surveillance 2018;4(2):e43
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. Foreward to special issue on health analytics. Health Care Management Science 2015;18(1):1
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Urquhart C, Tbaishat D. Reflections on the value and impact of library and information services. Performance Measurement and Metrics 2016;17(1):29
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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
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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
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Hartley BR, Elowitz E. Future Directions in Communication in Neurosurgery. World Neurosurgery 2020;133:474
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Huang M, ElTayeby O, Zolnoori M, Yao L. Public Opinions Toward Diseases: Infodemiological Study on News Media Data. Journal of Medical Internet Research 2018;20(5):e10047
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Mondal A, Cambria E, Das D, Hussain A, Bandyopadhyay S. Relation Extraction of Medical Concepts Using Categorization and Sentiment Analysis. Cognitive Computation 2018;10(4):670
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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
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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
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Jurdi ZR, Crosby JF, Harris JE, Harvey JB. A Closer Examination of the Patient Experience in the Ambulatory Space. Journal of Ambulatory Care Management 2020;43(1):89
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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
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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
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Liu J, Hou S, Evans R, Xia C, Xia W, Ma J. What Do Patients Complain About Online: A Systematic Review and Taxonomy Framework Based on Patient Centeredness. Journal of Medical Internet Research 2019;21(8):e14634
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Sidey-Gibbons JAM, Sidey-Gibbons CJ. Machine learning in medicine: a practical introduction. BMC Medical Research Methodology 2019;19(1)
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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
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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
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Liu N, Kauffman RJ. Enhancing healthcare professional and caregiving staff informedness with data analytics for chronic disease management. Information & Management 2021;58(2):103315
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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
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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 2021;80(15):23207
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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
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KESKİN , AYTEKİN YE. The Evaluation of Financial Participation Banking System in Turkey in the context of Sentiment Analysis. International Journal of Islamic Economics and Finance Studies 2019;
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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
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Gebbia V, Piazza D, Valerio MR, Borsellino N, Firenze A. Patients With Cancer and COVID-19: A WhatsApp Messenger-Based Survey of Patients’ Queries, Needs, Fears, and Actions Taken. JCO Global Oncology 2020;(6):722
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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
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Patel S, Cain R, Neailey K, Hooberman L. Public Awareness, Usage, and Predictors for the Use of Doctor Rating Websites: Cross-Sectional Study in England. Journal of Medical Internet Research 2018;20(7):e243
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Nemzer LR, Neymotin F. Concierge care and patient reviews. Health Economics 2020;29(8):913
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Oyebode O, Alqahtani F, Orji R. Using Machine Learning and Thematic Analysis Methods to Evaluate Mental Health Apps Based on User Reviews. IEEE Access 2020;8:111141
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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
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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
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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
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Sewalk KC, Tuli G, Hswen Y, Brownstein JS, Hawkins JB. Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study. Journal of Medical Internet Research 2018;20(10):e10043
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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
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Meyer J, Okuboyejo S. User Reviews of Depression App Features: Sentiment Analysis. JMIR Formative Research 2021;5(12):e17062
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