Degree correlations in signed social networks

TL;DR

This study examines how positive and negative relationships in online social networks influence degree correlations, revealing that positive links tend to connect similar degree nodes while negative links connect dissimilar ones.

Contribution

The paper introduces simple theoretical models to explain the emergence of assortative and disassortative patterns based on link sign in signed social networks.

Findings

Positive subnetworks are assortative by degree.

Negative subnetworks are disassortative by degree.

Models explain the conditions for observed patterns.

Abstract

We investigate degree correlations in two online social networks where users are connected through different types of links. We find that, while subnetworks in which links have a positive connotation, such as endorsement and trust, are characterized by assortative mixing by degree, networks in which links have a negative connotation, such as disapproval and distrust, are characterized by disassortative patterns. We introduce a class of simple theoretical models to analyze the interplay between network topology and the superimposed structure based on the sign of links. Results uncover the conditions that underpin the emergence of the patterns observed in the data, namely the assortativity of positive subnetworks and the disassortativity of negative ones. We discuss the implications of our study for the analysis of signed complex networks.