Ensemble of Opinion Dynamics Models to Understand the Role of the Undecided in the Vaccination Debate

TL;DR

This paper compares three opinion dynamics models to understand how the undecided population influences the vaccination debate on social networks, revealing anti-vax opinions spread more effectively and suggesting network strategies to contain misinformation.

Contribution

It introduces and compares three novel models capturing different undecided behaviors in vaccination debates, providing insights into opinion spread and containment strategies.

Findings

Anti-vax opinions spread more than pro-vax despite smaller initial size.

Undecided individuals are mainly located at the core of the social network.

Adding links in the network helps contain anti-vax opinions.

Abstract

We present three models used to describe the recruitment of the undecided population by pro-vax and no-vax factions. Starting from real-world data of Facebook pages, we compare three opinion dynamics models that catch different behaviours of the undecided population. The first one is a variation of the SIS model, where undecided position is considered indifferent. Neutrals can be "infected" by one of the two extreme factions, joining their side, and they "recover" when they lose interest in the debate and go back to neutrality. The second model is a three parties Voters model: neutral pages represent a centrist position. They lean their original ideas, that are different from both the other parties. The last is the Bilingual model adapted to the vaccination debate: neutral individuals are in agreement with both pro-, ad anti-vax factions, with a position of compromise between the extremes ("bilingualism''). If they have a one-sided neighbourhood, the convenience to agree with both parties comes out, and bi-linguists can become mono-linguists. Our results depicts an agreement between the three models: anti-vax opinion propagates more than pro-vax, thanks to an initial strategic position in the online social network (even if they start with a smaller population). While most of the pro-vaccines nodes are segregated in their own communities, no-vaccines ones are entangled at the core of the network, where the majority of undecided population is located. In the last section, we propose and compare some policies that could be applied on the network to prevent anti-vax overcome: they lead us to conclude that censoring strategies are not effective, as well as segregating scenarios based on unfollowing decisions, while the addition of links in the network favours the containment of the pro-vax domain, reducing the distance between pro-vaxxers and undecided population.