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Entropy Production in Stationary Social Networks

  • Haye Hinrichsen
  • Tobias Hoßfeld
  • Matthias Hirth
  • Phuoc Tran-Gia
Part of the Studies in Computational Intelligence book series (SCI, volume 476)

Abstract

Completing their initial phase of rapid growth social networks are expected to reach a plateau from where on they are in a statistically stationary state. Such stationary conditions may have different dynamical properties. For example, if each message in a network is followed by a reply in opposite direction, the dynamics is locally balanced. Otherwise, if messages are ignored or forwarded to a different user, one may reach a stationary state with a directed flow of information. To distinguish between the two situations, we propose a quantity called entropy production that was introduced in statistical physics as a measure for non-vanishing probability currents in nonequilibrium stationary states. The proposed quantity closes a gap for characterizing social networks. As major contribution, we present a general scheme that allows one to measure the entropy production in arbitrary social networks in which individuals are interacting with each other, e.g. by exchanging messages. The scheme is then applied for a specific example of the R mailing list.

Keywords

Social Network Entropy Production Mailing List Incoming Link Geiger Counter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Haye Hinrichsen
    • 1
  • Tobias Hoßfeld
    • 2
  • Matthias Hirth
    • 2
  • Phuoc Tran-Gia
    • 2
  1. 1.Department of Physics and AstronomyUniversity of WürzburgWürzburgGermany
  2. 2.Institute of Computer Science, Communication NetworksUniversity of WürzburgWürzburgGermany

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