The cohesiveness of blocks in social networks: Node connectivity and conditional density

By Douglas R. White, Frank Harary. 2001

350 citations recorded by the source corpus.

This study shows several ways that formal graph theoretic statements map patterns of network ties into substantive hypotheses about social cohesion. If network cohesion is enhanced by multiple connections between members of a group, for example, then the higher the global minimum of the number of independent paths that connect every pair of nodes in the network, the higher the social cohesion. The cohesiveness of a group is also measured by the extent to which it is not disconnected by removal of 1, 2, 3, . . . , k actors. Menger's Theorem proves that these two measures are equivalent. Within this graph theoretic framework, we evaluate various concepts of cohesion and establish the validity of a pair of related measures:.

Subfields: Management Science and Operations Research, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/ac9198fe1c5d8b2564780753fc949584e0a4a952

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In Management Science and Operations Research

In Statistical and Nonlinear Physics

Citations in the corpus

Community structure in social and biological networks (2001, background): “To this end, we have selected two datasets representing real-world networks for which the community structure is already known from other sources.”
NetCoMi: network construction and comparison for microbiome data in R (2020, neutral): “Presence/ absence of an edge Density Ratio of the actual number of edges in the network and the possible number of edges [87].”
Communities, modules and large-scale structure in networks (2011, neutral): “It has been claimed repeatedly that by examining the pattern of friendships depicted in the network (which was compiled before the split happened) one can predict the membership of the two faction”
The analysis of social networks (2008, background): “Still another cohesion concept is the k-connected component (White and Harary 2001): a maximal subset of actors mutually linked to one another by at least k node-independent paths (i.e., paths that involve disjoint sets of intermediary actors who also lie within the subset).”
A classification for community discovery methods in complex networks (2011, neutral): “Previously the traditional graph partitioning approach constructed communities by adding the strongest edges to an initially empty vertex set (as in hierarchical clustering [126]).”
The “New” Science of Networks (2004, background): “…to identifying community structure have tended to rely on some version partitioning the network into increasingly similar subsets of nodes, where pairwise similarity can be measured in terms of, for example, cohesion (Moody & White 2003, White & Harary 2001) or equivalence (Lorrain & White 1971).”