Message passing solutions in percolation identify reachability from cycles, not giant component membership, on any directed or undirected networks.
Marvel Universe looks almost like a real social network
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
abstract
We investigate the structure of the Marvel Universe collaboration network, where two Marvel characters are considered linked if they jointly appear in the same Marvel comic book. We show that this network is clearly not a random network, and that it has most, but not all, characteristics of "real-life" collaboration networks, such as movie actors or scientific collaboration networks. The study of this artificial universe that tries to look like a real one, helps to understand that there are underlying principles that make real-life networks have definite characteristics.
verdicts
UNVERDICTED 4representative citing papers
KSI-centrality is a new measure whose distribution independently distinguishes real networks from random and model networks beyond scale-freeness, with its normalized average bijectively setting the m parameter in Barabasi-Albert models.
A network generation model combining exponential probabilistic growth with vari-linear preferential attachment fits empirical degree distributions more accurately than traditional linear models and unifies several classical network properties.
Shannon-entropy metric quantifies effective cast size in movies and Jensen-Shannon divergence measures similarity between films, applied to predict MCU success.
citing papers explorer
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Message passing and cyclicity transition
Message passing solutions in percolation identify reachability from cycles, not giant component membership, on any directed or undirected networks.
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Capability centrality: the next step from scale-free property
KSI-centrality is a new measure whose distribution independently distinguishes real networks from random and model networks beyond scale-freeness, with its normalized average bijectively setting the m parameter in Barabasi-Albert models.
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Universal Network Generation Model via Exponential Probabilistic Growth and Vari-linear Preferential Attachment
A network generation model combining exponential probabilistic growth with vari-linear preferential attachment fits empirical degree distributions more accurately than traditional linear models and unifies several classical network properties.
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How the Avengers assemble: Ecological modelling of effective cast sizes for movies
Shannon-entropy metric quantifies effective cast size in movies and Jensen-Shannon divergence measures similarity between films, applied to predict MCU success.