Coevolution of Network Structure and Content

  • Teng C
  • Gong L
  • Livne A
 et al. 
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Abstract

As individuals communicate, their exchanges form a dy- namic network. We demonstrate, using time series analy- sis of communication in three online settings, that network structure alone can be highly revealing of the diversity and novelty of the information being communicated. Our ap- proach uses both standard and novel network metrics to characterize how unexpected a network configuration is, and to capture a network’s ability to conduct information. We find that networks with a higher conductance in link struc- ture exhibit higher information entropy, while unexpected network configurations can be tied to information novelty. We use a simulation model to explain the observed corre- spondence between the evolution of a network’s structure and the information it carries.

Author-supplied keywords

  • information networks
  • network evolution
  • social media

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Authors

  • C. Teng

  • L. Gong

  • A. Livne

  • C. Brunetti

  • L. Adamic

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