User Behaviors and User-Generated Content in Chinese Online Health Communities: Comparative Study

• Published in: Journal of medical Internet research 2021-12, Vol.23 (12), p.e19183-e19183
• Main Authors: Lei, Yuqi, Xu, Songhua, Zhou, Linyun
• Format: Article
• Language: English
• Subjects: Behavior; Breast cancer; Caregivers; China; Chronic illnesses; Clustering; Comparative studies; COVID-19; Diabetes; Disease Outbreaks; Humans; Lung cancer; Medical diagnosis; Mining; Original Paper; Policy making; Public Health; SARS-CoV-2; Social networks; Supporters; Topics; User behavior; Virtual communities
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/19183

Online health communities (OHCs) have increasingly gained traction with patients, caregivers, and supporters globally. Chinese OHCs are no exception. However, user-generated content (UGC) and the associated user behaviors in Chinese OHCs are largely underexplored and rarely analyzed systematically, forfeiting valuable opportunities for optimizing treatment design and care delivery with insights gained from OHCs. This study aimed to reveal both the shared and distinct characteristics of 2 popular OHCs in China by systematically and comprehensively analyzing their UGC and the associated user behaviors. We concentrated on studying the lung cancer forum (LCF) and breast cancer forum (BCF) on Mijian, and the diabetes consultation forum (DCF) on Sweet Home, because of the importance of the 3 diseases among Chinese patients and their prevalence on Chinese OHCs in general. Our analysis explored the key user activities, small-world effect, and scale-free characteristics of each social network. We examined the UGC of these forums comprehensively and adopted the weighted knowledge network technique to discover salient topics and latent relations among these topics on each forum. Finally, we discussed the public health implications of our analysis findings. Our analysis showed that the number of reads per thread on each forum followed gamma distribution (H =0, H =0, and H =0); the number of replies on each forum followed exponential distribution (adjusted R =0.946, adjusted R =0.958, and adjusted R =0.971); and the number of threads a user is involved with (adjusted R =0.978, adjusted R =0.964, and adjusted R =0.970), the number of followers of a user (adjusted R =0.989, adjusted R =0.962, and adjusted R =0.990), and a user's degrees (adjusted R =0.997, adjusted R =0.994, and adjusted R =0.968) all followed power-law distribution. The study further revealed that users are generally more active during weekdays, as commonly witnessed in all 3 forums. In particular, the LCF and DCF exhibited high temporal similarity (ρ=0.927; P