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Network characterization of the Entangled Model for sustainability indicators. Analysis of the network properties for scenarios.

Pavel VazquezJesús Antonio Del RíoKarla G CedanoJiska van DijkHenrik Jeldtoft Jensen
Published in: PloS one (2018)
Policy-makers require strategies to select a set of sustainability indicators that are useful for monitoring sustainability. For this reason, we have developed a model where sustainability indicators compete for the attention of society. This model has shown to have steady situations where a set of sustainability indicators are stable. To understand the role of the network configuration, in this paper we analyze the network properties of the Entangled Sustainability model. We have used the degree distribution, the clustering coefficient, and the interaction strength distribution as main measures. We also analyze the network properties for scenarios compared against randomly generated scenarios. We found that the stable situations show different characteristics from the unstable transitions present in the model. We also found that the complex emergent feature of sustainability shown in the model is an attribute of the scenarios, however, the randomly generated scenarios do not present the same network properties.
Keyphrases
  • climate change
  • healthcare
  • public health
  • mental health
  • computed tomography
  • magnetic resonance
  • machine learning
  • magnetic resonance imaging
  • rna seq
  • diffusion weighted imaging
  • neural network