Defines betweenness centrality in stochastic networks via absorbing Markov chain absorption times, estimated by Monte Carlo on random and real graphs.
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7 Pith papers cite this work. Polarity classification is still indexing.
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Develops a quantum-percolation DPC metric that ranks critical areas in transport networks by continuous propagation loss, applied to Sioux Falls and post-Irma Florida networks where it differs from classical percolation and other centrality measures.
Local 2- and 3-cycles enhance RNN computational capacity for Boolean functions, predicted by structural statistics, while adding interneurons boosts large networks.
A framework is introduced that links activist needs (minimal overhead, community building, safety, sustainability) to DSN affordances and is applied to compare Mastodon and Bluesky plus example communities.
A multiplex network model of cancer science collaborations indicates that US funding declines increase compensatory burdens on the EU and BRICS while creating opportunities for greater resilience through expanded international support from other nations.
Cross-boundary collaboration in open source is sustained by a thin carrier layer of contributors and repeat relationships that increase pull request acceptance rates from 42% to 87%.
Spectral thermodynamic analysis of virus-host networks in three species shows transition-like behavior under node removal, suggesting a framework for assessing structural stability.
citing papers explorer
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Betweenness Central Nodes Under Uncertainty: An Absorbing Markov Chain Approach
Defines betweenness centrality in stochastic networks via absorbing Markov chain absorption times, estimated by Monte Carlo on random and real graphs.
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Quantum percolation based dynamic propagation connectivity for critical-area identification in transport networks
Develops a quantum-percolation DPC metric that ranks critical areas in transport networks by continuous propagation loss, applied to Sioux Falls and post-Irma Florida networks where it differs from classical percolation and other centrality measures.
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Identifying structural design principles shaping the computational abilities of recurrent neural networks
Local 2- and 3-cycles enhance RNN computational capacity for Boolean functions, predicted by structural statistics, while adding interneurons boosts large networks.
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The Activist's Guide to the Decentralized Social Universe: A Framework for Exploring How Decentralized Social Networks Can Support Collective Action
A framework is introduced that links activist needs (minimal overhead, community building, safety, sustainability) to DSN affordances and is applied to compare Mastodon and Bluesky plus example communities.
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Declines in research funding and science ecosystem fragility
A multiplex network model of cancer science collaborations indicates that US funding declines increase compensatory burdens on the EU and BRICS while creating opportunities for greater resilience through expanded international support from other nations.
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Building Digital Societies as Ecosystems: How Recognition and Repeat Relationships Sustain Cross-Community Work in Open Source
Cross-boundary collaboration in open source is sustained by a thin carrier layer of contributors and repeat relationships that increase pull request acceptance rates from 42% to 87%.
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Thermodynamic stability and structural transitions in virus-host networks
Spectral thermodynamic analysis of virus-host networks in three species shows transition-like behavior under node removal, suggesting a framework for assessing structural stability.