The Impact of Network Flows on Community Formation in Models of Opinion Dynamics. Ghosh, R. & Lerman, K. Journal of Mathematical Sociology, 39:109–124, 2015.
The Impact of Network Flows on Community Formation in Models of Opinion Dynamics [link]Paper  abstract   bibtex   2 downloads  
We study dynamics of opinion formation in a network of coupled agents. As the network evolves to a steady state, opinions of agents within the same community converge faster than those of other agents. This framework allows us to study how network topology and network flow, which mediates the transfer of opinions between agents, both affect the formation of communities. In traditional models of opinion dynamics, agents are coupled via conservative flows, which result in one-to-one opinion transfer. However, social interactions are often nonconservative, resulting in one-to-many transfer of opinions. We study opinion formation in networks using one-to-one and one-to-many interactions and show that they lead to different community structure within the same network.
@ARTICLE{Ghosh15gmas,
  AUTHOR =       {Rumi Ghosh and Kristina Lerman},
  TITLE =        {The Impact of Network Flows on Community Formation in Models of Opinion Dynamics},
  JOURNAL =      {Journal of Mathematical Sociology},
  YEAR =         {2015},
  volume =       {39},
  number =       {},
  pages =        {109--124},
  month =        {},
  note =         {},
  keywords =     {social-networks},
  url={http://www.tandfonline.com/doi/pdf/10.1080/0022250X.2014.905776},
  abstract =     {We study dynamics of opinion formation in a network of coupled agents. As the network
evolves to a steady state, opinions of agents within the same community converge faster than
those of other agents. This framework allows us to study how network topology and
network flow, which mediates the transfer of opinions between agents, both affect the
formation of communities. In traditional models of opinion dynamics, agents are coupled
via conservative flows, which result in one-to-one opinion transfer. However, social
interactions are often nonconservative, resulting in one-to-many transfer of opinions.
We study opinion formation in networks using one-to-one and one-to-many interactions
and show that they lead to different community structure within the same network.}
  }

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