2 citations · 2 across the 2 of their papers we have counts for
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Centrality in dynamic competition networks
Anthony Bonato, Nicole Eikmeier, David F. Gleich +1
Competition networks are formed via adversarial interactions between actors. The Dynamic Competition Hypothesis predicts that influential actors in competition networks should have…
Triangle Preferential Attachment Has Power-law Degrees and Eigenvalues; Eigenvalues Are More Stable to Network Sampling
Nicole Eikmeier, David F. Gleich
Preferential attachment models are a common class of graph models which have been used to explain why power-law distributions appear in the degree sequences of real network data. O…
The HyperKron Graph Model for higher-order features
Nicole Eikmeier, Arjun S. Ramani, David F. Gleich
Graph models have long been used in lieu of real data which can be expensive and hard to come by. A common class of models constructs a matrix of probabilities, and samples an adja…
Dynamic Competition Networks: detecting alliances and leaders
Anthony Bonato, Nicole Eikmeier, David F. Gleich +1
We consider social networks of competing agents that evolve dynamically over time. Such dynamic competition networks are directed, where a directed edge from nodes to corre…
Coin-flipping, ball-dropping, and grass-hopping for generating random graphs from matrices of edge probabilities
Arjun S. Ramani, Nicole Eikmeier, David F. Gleich
Common models for random graphs, such as Erdős-Rényi and Kronecker graphs, correspond to generating random adjacency matrices where each entry is non-zero based on a large matrix o…