Analysis of Information Dissemination in Large-Scale Networks Using Local Structural Information

Computer Science – Social and Information Networks

Scientific paper

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Facebook datasets and related MATLAB code can be found in http://sites.google.com/site/victormpreciado/publications

Scientific paper

The intricate structure of many large-scale networked systems has attracted the attention of the scientific community, leading to many results attempting to explain the relationship between a network structural features and the performance of processes taking place in the network. A common approach to study the relationship between structure and performance is to use synthetic network models in which structural properties of interest, such as degree distributions, are prescribed. Although very common, this approach presents a major flaw: Synthetic network models implicitly induce many structural properties that are not directly controlled and can be relevant to the network performance. Therefore, it is difficult to draw conclusions about the role of a particular structural property in a real network using synthetic models. In this paper, we propose an alternative approach to overcome this flaw. Our approach is not based on synthetic models, instead, we use algebraic graph theory and convex optimization to study how structural properties constrain performance metrics of the network. We formulate this novel approach by analyzing the role of network structural properties in epidemic-style processes of information dissemination in networked systems. We illustrate our approach with nontrivial numerical simulations on an online social network.

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