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Random graph generation is an important tool for studying large complex networks. Despite abundance of random graph models, constructing models with application-driven constraints is poorly understood. In order to advance state-of-the-art in this area, we focus on random graphs without short...
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network formation. While the physics/applied mathematics approach is capable of reproducing most observed networks, it does … results with those obtained in sociology. -- Random graph ; game theory ; centrality measures ; network formation ; weak and …
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