Coevolution of network structure and content

Authors:
Chun-Yuen Teng;Liuling Gong;Avishay Livne Eecs;Celso Brunetti;Lada Adamic
Affiliations:
University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;Carey Business School, Johns Hopkins, Baltimore, MD;University of Michigan, Ann Arbor, MI
Venue:
Proceedings of the 3rd Annual ACM Web Science Conference
Year:
2012

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Abstract

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.