A new measure for community structures through indirect social connections

Based on an expert systems approach, the issue of community detection can be conceptualized as a clustering model for networks. Building upon this further, community structure can be measured through a clustering coefficient, which is generated from the number of existing triangles around the nodes over the number of triangles that can be hypothetically constructed. This paper provides a new definition of the clustering coefficient for weighted networks under a generalized definition of triangles. Specifically, a novel concept of triangles is introduced, based on the assumption that, should the aggregate weight of two arcs be strong enough, a link between the uncommon nodes can be induced. Beyond the intuitive meaning of such generalized triangles in the social context, we also explore the usefulness of them for gaining insights into the topological structure of the underlying network. Empirical experiments on the standard networks of 500 commercial US airports and on the nervous system of the Caenorhabditis elegans support the theoretical framework and allow a comparison between our proposal and the standard definition of clustering coefficient

The Emergence of Roles in Large-Scale Networks of Communication

Communication through social media mediates coordination and information diffusion across a range of social settings. However, online networks are large and complex, and their analysis requires new methods to summarize their structure and identify nodes holding relevant positions. We propose a method that generalizes the sociological theory of brokerage, originally devised on the basis of local transitivity and paths of length two, to make it applicable to larger, more complex structures. Our method makes use of the modular structure of networks to define brokerage at the local and global levels. We test the method with two different data sets. The findings show that our approach is better at capturing role differences than alternative approaches that only consider local or global network features