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Structural Cohesion: Visualization and Heuristics for Fast Computation
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The structural cohesion model is a powerful theoretical conception of cohesion in social groups, but its diffusion in empirical literature has been hampered by operationalization and computational problems. In this paper we start from the classic definition of structural cohesion as the minimum number of actors who need to be removed in a network in order to disconnect it, and extend it by using average node connectivity as a finer grained measure of cohesion. We present useful heuristics for computing structural cohesion that allow a speed-up of one order of magnitude over the algorithms currently available. We analyze three large collaboration networks (co-maintenance of Debian packages, co-authorship in Nuclear Theory and High-Energy Theory) and show how our approach can help researchers measure structural cohesion in relatively large networks. We also introduce a novel graphical representation of the structural cohesion analysis to quickly spot differences across networks.
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Cited by 1 Pith paper
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Experimental Analysis and Evaluation of Cohesive Subgraph Discovery
A systematic empirical comparison of 14 cohesive subgraph models shows truss-based and combined models find denser subgraphs, while core-based models return larger, more interpretable ones.
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