Understanding the Engagement and Interaction of Superusers and Regular Users in UK Respiratory Online Health Communities: Deep Learning–Based Sentiment Analysis
Network and sentiment analyses provide insight into the key sustaining role of superusers in respiratory OHCs, showing they tend to write and trigger regular users' posts characterized by positive sentiment.
Authors
- Xiancheng Li (ORCID: https://orcid.org/0009-0003-3734-1634)
- Neil Coulson (ORCID: https://orcid.org/0000-0001-9940-909X)
- Gabriella Pasi (ORCID: https://orcid.org/0000-0002-6080-8170)
- Marco Viviani (ORCID: https://orcid.org/0000-0002-2274-9050)
- Anna De Simoni (ORCID: https://orcid.org/0000-0001-6955-0885)
- Emanuela Vaghi
Institutions
- University of Nottingham (GB)
- Queen Mary University of London (GB)
- London School of Business and Management (GB)
- Asthma UK (GB)
- University of Milano-Bicocca (IT)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-02-13
- DOI
- https://doi.org/10.2196/56038
- Primary Topic
- Social Media in Health Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Queen Mary University of London
- National Institute for Health and Care Research
- Department of Health and Social Care
- Asthma and Lung UK
- Asthma UK Centre for Applied Research