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- W1640830400 abstract "The Naming Games (NG) are agent-based models for agreement dynamics, peer pressure and herding in social networks, and protocol selection in autonomous ad-hoc sensor networks. By introducing a small noise term to the NG, the resulting Markov Chain model called Noisy Naming Games (NNG) are ergodic, in which all partial consensus states are recurrent. By using Gibbs-Markov equivalence we show how to get the NNG's stationary distribution in terms of the local specification of a related Markov Random Field (MRF). By ordering the partially-synchronized states according to their Gibbs energy, taken here to be a good measure of social tension, this method offers an enhanced method for community-detection in social interaction data. We show how the lowest Gibbs energy multi-name states separate and display the hidden community structures within a social network." @default.
- W1640830400 created "2016-06-24" @default.
- W1640830400 creator A5072888915 @default.
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- W1640830400 date "2010-08-24" @default.
- W1640830400 modified "2023-09-27" @default.
- W1640830400 title "Noise in Naming Games, partial synchronization and community detection in social networks" @default.
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- W1640830400 hasPublicationYear "2010" @default.
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