Understanding user interaction patterns in health social media

Internet users are becoming increasingly social in their online information behavior, as shown by a growing trend of social media adoption in the past decade. Social interaction patterns in this new space are governed by the technological affordances in the infrastructure and membership to the community, yet at times also by individual emotional needs for seeking social support. In the consumer health domain, social networking technology and consumer health information needs combine to show that even within the same community, relationships are not expressed in the same manner across various computer mediated communication (CMC) formats. The motivation for this research comes from an increasing need to understand the patterns of social interactions online, especially of e-patients using the Internet as a health resource. Frequently, e-patients use social networking platforms to teach each other about conditions and treatments (Civan and Pratt, 2007; Wright and Bell, 2003). Social networking sites are predicted to increase in popularity as a way for people to socialize online as an extension of their physical environment. Online community tools include the popular text-based communication formats such as posting status updates, discussion boards and profile pages. While many previous studies of online support communities identified sociability factors such as types of social support (i.e. informational support, emotional support) exchanged in online support groups and health outcomes, there is a gap in research literature concerning the design of software interface architecture. The central focus of this research investigated the impact of software features on online supportive communication behavior across multiple computer-mediated communication (CMC) formats. This research contributes insights to opportunities for design and implementation of social media technologies for online health support communities; scholarly literature regarding online support communities, and inform policy makers who determine parameters for both design and management of online health support communities. The outcome of this study can contribute to improving online intervention programs by targeting specific functions of social network sites.