Social capital in an online health community: Network features and impact on breast cancer patients

This dissertation investigates how breast cancer patients are connected in a computer-mediated social support (CMSS) group and why the online social relationship matters to cancer patients' health outcomes. Specifically, it constructs online social networks to investigate how social relationships build in a CMSS group and what kinds of social support are exchanged through these electronic social ties. Using social network analysis, this study calculates a person's network size and centrality as measures of individual-level social capital. These social capital measures reflect the degree to which group members are in an advantageous position within the social networks to gain the valued resources, i.e., emotional and informational support. As a result, these online networks allow for an examination of the effects of social capital on psychological health benefits – perceived bonding, information competence, and coping strategies.;To that end, this dissertation employs an innovative methodology – combining computer-aided content analysis data with individual action usage log data. This methodological approach allows us to construct online social networks based on message expression and reception with great precision, and furthermore, distinguish between different types of social support networks, such as emotional support networks and informational support networks. In addition, I constructed the online social networks with two distinct communication models, the broadcasting and narrowcasting models, in order to optimally investigate the communication patterns that are occurring in online discussion groups.;The results shed crucial insight into our understanding of how CMSS groups can contribute to improved psychological health outcomes for breast cancer patients. First, I demonstrated that the perceived availability of social support was negatively related to network size in the broadcasting model, and the perceived family cohesion was negatively associated with network centrality in the narrowcasting model. Second, based on the concept of social capital, I showed the positive effects of an individual's network size and centrality on her health outcomes, such as perceived bonding, information competence, and coping strategies. Consequently, this dissertation provides a more concrete approach to overcoming the limitations of buffering and main effect models for CMSS group effects. Implications of the findings for fields of health communication are discussed.