Structural Properties of Ego Networks

TL;DR

This paper investigates the structural properties of ego networks in social networks, revealing how local views differ from global network features and proposing methods to correct biases from incomplete local information.

Contribution

It provides empirical and mathematical analysis of ego network structures and their relation to global network properties, highlighting biases and correction methods.

Findings

Ego networks often differ significantly from global network structure.

Structural features in ego networks can suffer from paradoxes similar to static attributes.

Methods to quantify and correct biases from local information are proposed.

Abstract

The structure of real-world social networks in large part determines the evolution of social phenomena, including opinion formation, diffusion of information and influence, and the spread of disease. Globally, network structure is characterized by features such as degree distribution, degree assortativity, and clustering coefficient. However, information about global structure is usually not available to each vertex. Instead, each vertex's knowledge is generally limited to the locally observable portion of the network consisting of the subgraph over its immediate neighbors. Such subgraphs, known as ego networks, have properties that can differ substantially from those of the global network. In this paper, we study the structural properties of ego networks and show how they relate to the global properties of networks from which they are derived. Through empirical comparisons and mathematical derivations, we show that structural features, similar to static attributes, suffer from paradoxes. We quantify the differences between global information about network structure and local estimates. This knowledge allows us to better identify and correct the biases arising from incomplete local information.