Coevolution of Network Structure and Content

TL;DR

This paper investigates how the evolving structure of communication networks relates to the diversity and novelty of information exchanged, using time series analysis and network metrics across online settings.

Contribution

It introduces a novel approach combining standard and new network metrics to link network structure with information diversity and novelty, supported by empirical analysis and simulation.

Findings

Higher conductance networks have greater information entropy

Unexpected network configurations are associated with information novelty

Network evolution correlates with changes in information content

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.