Xin Ming Tu, PhD, Ann Marie White and Naiji Lu (Editors)
University of Rochester, NY, USA

Series: Media and Communications – Technologies, Policies and Challenges
BISAC: TEC041000

Social networking focuses on social relationships (e.g., friendships) diagrammed as nodes (points) and links (ties or edges between points). Social network analysis (SNA) examines features of such relationships within a social networking system, including how such social interactions change over time. SNA can measure and map “connectedness” or “flow” (e.g., information, resources, etc.) within and across individuals, groups, and organizations. SNA can examine these ties in virtual- or geo-temporal spaces – yielding rich mixed methods possibilities and wide application to a host of scientific phenomena.

The advent of social media established a cultural meme that carries social network concepts to broader public audiences, and that reinforces SNA’s path to be a powerful interdisciplinary approach. Google Ngram viewer shows the use of “social network analysis” in the corpus of books burgeoned in the late 1960s, and has continued to grow exponentially since the 1990s. The conceptual and methodological reach now extends both widely – across scientific disciplines – and deeply — as field advances arise with the rapid pace of new inquiries.
Facing this tremendous promulgation and diversification of SNA, this book distills essential frontiers across fields. Introducing emerging issues in the application of social network theory and SNA, and how these can or will be addressed, each chapter illuminates new trends or applications of a social network approach that can have wide potential impact in other disciplines. Conceptual advances (e.g., applying the concepts of social networks such as peer influence on disease management and treatment adherence), as well as novel analytic approaches for studying properties of social networks are highlighted.

As SNA ideas spread and find fertile ground within respective fields, the potential and need for scientists to assemble multidisciplinary teams becomes critical. Taken together, the selected chapters privy a reader to a picture of leading edges of social network analytic approaches that can be useful to orient oneself as these teams take shape. These chapters point out that much potential and work remains to further develop this method, work that can be cross-fertilized through multidisciplinary team building. This volume demonstrates topics where the next generation of SNA concepts and methods can be propelled if interdisciplinary teams are fostered. This book illustrates both the breadth and depth of SNA, and is inspiring for readers who are interested in learning or applying social network thinking and analysis in their investigations. (Imprint: Nova)