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I see two concerns with current conceptions of cohesion:

1. Are overlaps allowed or made sense of?

Most methods allow overlap, but in their application there is very little mentioned about the phenomenon of overlapping. Is it an accident? Does it have benefits? Are there meaningful connections to agency?

2. Does it work with dynamic data?

Most methods are incapacitated in a dynamic framework. Let's say a dense, cohesive group A stays the same between t1 and t2 (same members, and the same ties among them). Now, most methods (including most new ones like Moody and White) would not recognize that group A stayed the same, if the network environment changes (it becomes denser or sparser for example). In other words, I see no other solution in a dynamic framework beyond local algorithms (like the clique percolation method). Otherwise how do you separate network change from methodological artifact?  

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