Information spreading in a large population of active transmitters and passive receivers

TL;DR

This paper models message spread in large populations with active transmitters and passive receivers, deriving approximations for broadcast times and analyzing the impact of transmitter fraction on propagation speed.

Contribution

It introduces a stochastic model capturing the dynamics of information spread with mixed transmitter and receiver roles, providing new approximations and dependence structures.

Findings

Approximate broadcast and passage times for large populations

Transmitter fraction significantly affects propagation speed

Dependence structure characterized by Gumbel and logistic distributions

Abstract

This paper discusses a simple stochastic model for the spread of messages in a large population with two types of individuals: transmitters and receivers. Transmitters, after receiving the message, start spreading copies of the message to their neighbors. Receivers may receive the message, but will never spread it further. We derive approximations of the broadcast time and the first passage times of selected individuals in populations of size tending to infinity. These approximations explain how much the fact that only a fraction of the individuals are transmitters slows down the propagation of information. Our results also sharply characterize the statistical dependence structure of first passage times using Gumbel and logistic distributions of extreme value statistics.