Title: Case studies in network community detection,
Abstract: Community structure describes the organization of a network into subgraphs
that contain a prevalence of edges within each subgraph and relatively few
edges across boundaries between subgraphs. The development of
community-detection methods has occurred across disciplines, with numerous and
varied algorithms proposed to find communities. As we present in this Chapter
via several case studies, community detection is not just an "end game" unto
itself, but rather a step in the analysis of network data which is then useful
for furthering research in the disciplinary domain of interest. These
case-study examples arise from diverse applications, ranging from social and
political science to neuroscience and genetics, and we have chosen them to
demonstrate key aspects of community detection and to highlight that community
detection, in practice, should be directed by the application at hand.