Abstract
We investigate the technical problem of community and clique detection in investor network. We introduce a pruning technique for investor clique enumeration based on specific economic and financial contexts. It can be incorporated into the central clique solver to reduce the computing time and improve the clique-based community detection method. Furthermore, we present several use cases in the study on investor behavior.
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