Network Models of Minority Opinion Spreading: A Computational Approach for Studying Possible Scenarios of Complex Social Contagion on Vaccination Behaviour

Abstract

Human behaviour plays a central role in the development and spread of epidemics, but also the opinions and attitudes that give rise to them. Hence, it is necessary to understand the social dynamics that are susceptible to contribute in the formation and spreading of opinions that are susceptible to affect collective decision making processes and behavioural changes. Specifically, individuals’ decision making processes related with vaccination have a significant impact on the control of infectious diseases. In fact, the prevention of disease contagion requires the vaccination coverage of a certain population to be above the level of herd immunity threshold. Therefore public health is closely related to these behavioural dynamics. This study aims to analyse the process of minority opinion spreading regarding vaccination through the computational analysis of different simulated scenarios designed with agent-based modelling, and giving response to three basic questions: (1) how the structure of social networks can affect the spread of minority opinion towards vaccination; (2) how committed or loyal agents can influence in this process (i.e. agents predisposition towards certain alternative: taking the vaccinate or not); and (3) how mass media action, as a contextual (or external) factor, might vary agents’ opinions and network composition. This study seeks to develop new and innovative models, based on computational social sciences, that contribute to the explanation and understanding of the collective dynamics of minority opinion contagion, and also to explain their potential impact on health and social behaviour under four basic simulated scenarios: (1) random individual contagion; (2) learning-based contagion; (3) preferential attachment; (4) preferential attachment and selective exposure (dual climate of opinion).