Spreading gossip in social networks

TL;DR

This paper introduces a model for gossip spreading in social networks, analyzing how information propagates and the influence of network structure on gossip likelihood, with applications to real-world social data.

Contribution

It presents a novel model quantifying gossip spread and compares its dynamics across various real and synthetic network types.

Findings

Friendship connections increase gossip probability

Spread factor effectively measures gossip dynamics

Model applicable to diverse network structures

Abstract

We study a simple model of information propagation in social networks, where two quantities are introduced: the spread factor, which measures the average maximal fraction of neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.