Information Flow in Social Groups

TL;DR

This paper investigates how information spreads within social groups, considering the influence of social proximity and attribute similarity, and demonstrates that information dissemination is limited in scale-free networks with attribute correlation.

Contribution

It introduces a model accounting for attribute similarity decay with social distance and validates it through organizational message spread measurements and numerical experiments.

Findings

Information spread is limited in networks with attribute similarity decay.

A finite threshold exists for epidemic-like information dissemination.

Organizational measurements support the model's predictions.

Abstract

We present a study of information flow that takes into account the observation that an item relevant to one person is more likely to be of interest to individuals in the same social circle than those outside of it. This is due to the fact that the similarity of node attributes in social networks decreases as a function of the graph distance. An epidemic model on a scale-free network with this property has a finite threshold, implying that the spread of information is limited. We tested our predictions by measuring the spread of messages in an organization and also by numerical experiments that take into consideration the organizational distance among individuals.