Application of Information Theory in Rumor Spreading Modeling Considering Polarization in Complex Networks

TL;DR

This paper introduces a novel information-theoretic model for simulating rumor spreading in complex networks, accounting for polarization, memory, and ideological proximity, using entropy and Jensen-Shannon divergence.

Contribution

It presents a new computational model that incorporates polarization and individual memory into rumor spreading dynamics on scale-free networks.

Findings

Model effectively simulates opinion dissemination with polarization effects.

Incorporates entropy and Jensen-Shannon divergence for realistic information spread.

Highlights the impact of ideological proximity on rumor propagation.

Abstract

It is proposed a model that makes use of the Entropy concept and the Jensen-Shannon information divergence function to simulate computationally the dissemination of opinions on a Barab\'asi-Albert (BA) scale-free network. The simulation considers individual memory, ideological proximity between individuals, and distortion influenced by polarization.