Network Dynamics: How Can We Find Patients Like Us?

Social networks have been shown to affect health. Because online social networking makes it easier for individuals to interact with experientially similar others in regard to health issues and to exchange social support, there has been an increasing effort to understand how networks function. Nevertheless, little attention has been paid to how these networks are formed. In this paper, we examine the driving forces behind patients’ social network formation and evolution. We argue that patients’ health-related traits influence their social connections and that the patients’ network layout is shaped by their cognitive capabilities and their network embeddedness. By studying longitudinal data from 1,322 individuals and their communication ties in an online healthcare social network, we find that firsthand disease experience, which provides knowledge of the disease, increases the probability that patients will find experientially similar others and establish communication ties. Patients’ cognitive abilities, including the information load that they can process and the range of social ties that they can manage, however, limit their network growth. In addition, we find that patients’ efforts to reach out for additional social resources are associated with their embeddedness in the network and the cost of maintaining connections. Practical implications of our findings are discussed.

• 저널Information Systems Research · 26(3) · 496–512
• 토픽Complex Network Analysis Techniques · Statistical and Nonlinear Physics
• DOI10.1287/isre.2015.0585
• 저자Lu Yan, Jianping Peng, Yong Tan