Absolute centrality in a signed Friedkin-Johnsen based model: a graphical characterisation of influence

TL;DR

This paper introduces an absolute centrality measure for signed networks with stubborn agents, using a graphical approach to quantify influence and account for network topology, stubbornness, and antagonism.

Contribution

It proposes a novel absolute centrality measure applicable to any network structure, incorporating stubbornness and antagonism effects in influence analysis.

Findings

The measure captures influence dynamics in signed networks.

Network topology significantly affects agents' influence.

Stubbornness can alter agents' influence status.

Abstract

This paper studies the evolution of opinions governed by a Friedkin Johnsen (FJ) based model in arbitrary network structures with signed interactions. The agents contributing to the opinion formation are characterised as being influential. Initially, the agents are classified as opinion leaders and followers based on network connectivity and the nature of interactions. However, the addition of stubbornness leads to interesting behaviours wherein a non influential agent can now become influential and vice versa. Thereafter, a signal flow graph (SFG) based method is proposed to quantify the influence of an influential agents' opinions. Additionally, it helps illustrate the role played by network topology in shaping the final opinions of the agents. Based on this analysis, the absolute centrality measure is proposed to determine the overall influence of all the agents in the network. Unlike most of the existing measures, it is applicable to any network structure and considers the effect of stubbornness and antagonism. Examples are presented throughout the paper to illustrate and validate these results.