IDENTIFYING HIDDEN COALITIONS IN THE US HOUSE OF REPRESENTATIVES BY OPTIMALLY PARTITIONING SIGNED NETWORKS BASED ON GENERALIZED BALANCE

Identifying hidden coalitions in the US House of Representatives by optimally partitioning signed networks based on generalized balance

Abstract In network science, identifying optimal partitions of a signed network into internally cohesive and mutually divisive clusters based on generalized balance theory is computationally challenging.We reformulate and generalize two binary linear programming models that tackle this challenge, demonstrating their practicality by applying them to

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