How polarization can provide an increase in content dissemination amongst the highly ranked influencers

TL;DR

This paper models how polarization influences content dissemination among influential users, showing that polarization increases response disparity and affects influence dynamics in social networks.

Contribution

It extends the Dynamic Communicators model to include polarization effects, providing insights into influence and content spread in polarized networks.

Findings

Polarization increases response rate disparity.

Lack of polarization leads to more level discussion networks.

Polarization affects influence distribution among users.

Abstract

This work extends a model of simulating influence in a network of stochastic edge dynamics to account for polarization. The model built upon is termed Dynamic Communicators and seeks to understand the process which produces low volume, high influence amongst users. This model is extended to introduce the effects polarization. The fundamental assumption of the model is that a parameter of importance governs the rate of message responsiveness. With the introduction of relative incremental changes according to the response incurred in adjacent nodes receiving content, the changes in the power brokerage of a network can be examined. This provides a content agnostic interpretation for the desire to proliferate content amongst peers. From the results of the simulations, the analysis shows that a lack of polarization incrementally develops a more level discussion network with more even response rates whereas the polarization introduction leads to a gradual increase in response rate disparity.