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

Background: 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. Objective: 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. Methods: 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. Results: Our analysis showed that the number of reads per thread on each forum followed gamma distribution (H-L=0, H-B=0, and H-D=0); the number of replies on each forum followed exponential distribution (adjusted R-L(2) =0.946, adjusted R-B(2)=0.958, and adjusted R-D(2) =0.971); and the number of threads a user is involved with (adjusted R-L(2)=0.978, adjusted R-B(2)=0.964, and adjusted R-D(2)=0.970), the number of followers of a user (adjusted R-L(2)=0.989, adjusted R-B(2)=0.962, and adjusted R-D(2)=0.990), and a user's degrees (adjusted R-L(2)=0.997, adjusted R-B(2)=0.994, and adjusted R-D(2)=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 (rho=0.927; P<.001) in terms of the relative thread posting frequencies during each hour of the day. Besides, the study showed that all 3 forums exhibited the small-world effect (mean sigma(L)=517.15, mean sigma(B)=275.23, and mean sigma(D)=525.18) and scale-free characteristics, while the global clustering coefficients were lower than those of counterpart international OHCs. The study also discovered several hot topics commonly shared among the 3 disease forums, such as disease treatment, disease examination, and diagnosis. In particular, the study found that after the outbreak of COVID-19, users on the LCF and BCF were much more likely to bring up COVID-19-related issues while discussing their medical issues. Conclusions: UGC and related online user behaviors in Chinese OHCs can be leveraged as important sources of information to gain insights regarding individual and population health conditions. Effective and timely mining and utilization of such content can continuously provide valuable firsthand clues for enhancing the situational awareness of health providers and policymakers.

Automated summary

This study systematically analyzed the user-generated content and associated behaviors in two popular online health communities in China. The findings indicated distinct distribution patterns in user activities, higher activity levels on weekdays, and shared hot topics among the three disease forums. Leveraging such information can provide valuable insights for improving healthcare delivery and situational awareness.