JMIR Publications

ABSTRACT

Background:

Online Health Communities (OHCs) have increasingly gained traction with patients, caregivers, and supporters all over the world. Chinese OHCs are no exceptions. Rich information such as patient conditions, behaviors, and outcomes is openly and abundantly shared in OHCs, providing unprecedented opportunities to acquire fine-grained, multifaceted, and timely situational awareness about patient experiences and quality of care delivered. However, such 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 utilizing insights gained from OHCs.

Objective:

This paper aims to reveal both shared and distinct characteristics of two popular OHCs in China through systematically and comprehensively analyzing their UGC and the associated user behaviors.

Methods:

We focus on analyzing two Chinese OHCs, Mijian and Sweet Home, in this study due to their predominant popularity among Chinese patients and health-conscious online users. In particular, we concentrate 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 three diseases among Chinese patients and their prevalence on Chinese OHCs in general. Our analysis explores key user activities, small-world effect and scale-free characteristics of each social network respectively corresponding to one of the three focus forums. We examine the UGC of these forums comprehensively and adopted the Weighted Knowledge Network (WKN) technique to discover salient topics and latent relations among these topics on each forum. Finally, we discuss public health implications of our analysis findings.

Results:

Our analysis shows that the number of reads per thread on each forum follows the Gamma distribution (H_L=0, H_B=0, H_D=0), the number of replies on each forum follows the exponential distribution (\bar{R}_{L}^{2}=0.946, \bar{R}_{B}^{2}=0.958, \bar{R}_{D}^{2}=0.971), the number of threads a user is involved with (\bar{R}_{L}^{2}=0.978, \bar{R}_{B}^{2}=0.964, \bar{R}_{D}^{2}=0.970), the number of a user’s followers (\bar{R}_{L}^{2}=0.989, \bar{R}_{B}^{2}=0.962, \bar{R}_{D}^{2}=0.990), and a user’s degrees (\bar{R}_{L}^{2}=0.997, \bar{R}_{B}^{2}=0.994 , \bar{R}_{D}^{2}=0.968) all follow the power-law distribution. The study further reveals that users are generally more active during weekdays, as commonly witnessed on all three forums. In particular, the two cancer forums, LCF and DCF, exhibit a high temporal similarity of \rho =0.927 (P<.001) in terms of the relative frequencies of posting for threads during each hour of the day. Besides, the study shows that all three forums exhibit the small-world effect (\sigma_{L}=522.07, \sigma_{B}=286.37, \sigma_{D}=529.07) and scale-free characteristics, while the global clustering coefficients of them are lower than those of counterpart international OHCs. The study also discovers several hot topics commonly shared among the three disease forums, such as disease treatment, disease examination, and diagnosis. In particular, the study finds out that after the outbreak of COVID-19, users on LCF and BCF are much more likely to bring up COVID-related issues while discussing their medical issues.

Conclusions:

UGC and their related online user behaviors in Chinese OHCs can be leveraged as an important source 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 situational awareness of health providers and policymakers.