A Computational Model and Convergence Theorem for Rumor Dissemination in Social Networks

TL;DR

This paper introduces a computational model for rumor spread in social networks, analyzing how societal homogeneity influences rumor convergence, with implications for controlling misinformation dissemination.

Contribution

It presents a novel computational model incorporating rumor features and societal factors, and proves a convergence theorem linking societal homogeneity to rumor spread behavior.

Findings

Homogeneity of society is necessary for rumor convergence.

The model captures the influence of agent desires and trust networks.

Theoretical analysis provides conditions for rumor stabilization.

Abstract

The spread of rumors, which are known as unverified statements of uncertain origin, may cause tremendous number of social problems. If it would be possible to identify factors affecting spreading a rumor (such as agents' desires, trust network, etc.), then this could be used to slowdown or stop its spreading. A computational model that includes rumor features and the way a rumor is spread among society's members, based on their desires, is therefore needed. Our research is centering on the relation between the homogeneity of the society and rumor convergence in it and result shows that the homogeneity of the society is a necessary condition for convergence of the spreading rumor.