Influence of trust in the spreading of information

TL;DR

This paper investigates how trust influences information diffusion on networks, showing that trust dynamics and memory significantly affect spreading outcomes in a multiplex network model.

Contribution

It introduces a trust-based, multiplex network model incorporating memory effects and analyzes how trust impacts information spread, advancing understanding of rational decision influences.

Findings

Memory reduces information diffusion when increased.

Trustable acquaintances significantly promote spreading.

Trust dynamics alter diffusion patterns in network models.

Abstract

The understanding and prediction of information diffusion processes on networks is a major challenge in network theory with many implications in social sciences. Many theoretical advances occurred due to stochastic spreading models. Nevertheless, these stochastic models overlooked the influence of rational decisions on the outcome of the process. For instance, different levels of trust in acquaintances do play a role in information spreading, and actors may change their spreading decisions during the information diffusion process accordingly. Here, we study an information-spreading model in which the decision to transmit or not is based on trust. We explore the interplay between the propagation of information and the trust dynamics happening on a two-layer multiplex network. Actors' trustable or untrustable states are defined as accumulated cooperation or defection behaviors, respectively, in a Prisoner's Dilemma set up, and they are controlled by a memory span. The propagation of information is abstracted as a threshold model on the information-spreading layer, where the threshold depends on the trustability of agents. The analysis of the model is performed using a tree approximation and validated on homogeneous and heterogeneous networks. The results show that the memory of previous actions has a significant effect on the spreading of information. For example, the less memory that is considered, the higher is the diffusion. Information is highly promoted by the emergence of trustable acquaintances. These results provide insight into the effect of plausible biases on spreading dynamics in a multilevel networked system.