Analyzing Patient Experience on Weibo: Machine Learning Approach to Topic Modeling and Sentiment Analysis
Hospital administrators and clinicians should consider the value of social media and pay attention to what patients and their family members are communicating on social media. To increase the utility of these data, a machine learning algorithm can be used for topic modeling. The results of this study highlighted the interpersonal and functional aspects of care, especially the interpersonal aspects, which are often the "moment of truth" during a service encounter in which patients make a critical evaluation of hospital services.
Authors
- Yuxia Zhang (ORCID: https://orcid.org/0000-0003-4419-7004)
- Yichen Kang (ORCID: https://orcid.org/0009-0003-2216-3820)
- Zhiyun Shen (ORCID: https://orcid.org/0009-0001-8646-8696)
- Yuchen Tao (ORCID: https://orcid.org/0009-0007-3517-4317)
- Tingyu Guan (ORCID: https://orcid.org/0009-0001-7629-2076)
- Xiao Chen (ORCID: https://orcid.org/0000-0002-9476-812X)
Institutions
- Sun Yat-sen University (CN)
- Fudan University (CN)
- Zhongshan Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2024-11-29
- DOI
- https://doi.org/10.2196/59249
- Citations
- 7
- Primary Topic
- Patient Satisfaction in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 5.95