Coevolution of Network Structure and Content
  As individuals communicate, their exchanges form a dynamic network. We demonstrate, using time series analysis 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 approach 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 structure exhibit higher information entropy, while unexpected network configurations can be tied to information novelty. We use a simulation model to explain the observed correspondence between the evolution of a network's structure and the information it carries. 
Chun-Yuen Teng, Liuling Gong, Avishay Livne, Celso Brunetti and Lada   A. Adamic
cs.SI physics.soc-ph