Localized seeding for triggering the global social contagion in higher-order spatial networks

Extensive research has explored the contagion dynamics of social behaviors on higher-order spatial networks and uncovered many important findings, most of which are based on random seed strategies. In this study, we propose a social contagion model on higher-order spatial networks driven by local seeds, examining the impact of the network’s spatial structure on contagion modes and speeds. Previous research has suggested that clustered networks are more conducive to the diffusion of behavior. However, we find that excessively clustered networks inhibit behavior spread under local seed strategies. In highly clustered networks, individuals experience stronger social reinforcement; however, this also creates redundant connections, causing contagion to remain localized and preventing it from spreading over longer distances. Therefore, behavior diffusion is most effective when the network structure strikes a balance between social reinforcement and spatial distance, thus maximizing the synergy between low- and higher-order contagion.