Social contagion on higher-order networks: The effect of relationship strengths

We study the role and impact of interpersonal relationships on the dissemination of information, emotions, and behaviors through social higher-order networks. Namely, we introduce a novel model that explicitly accounts for strong and weak relationships on social contagion, and that integrates binary and ternary interactions among individuals. The model captures the dynamics of complex group interactions, and the differential impact that these relationship strengths have on the spread of contagion within various network structures. Our study reveals that in non-preferential structures, strong relationships significantly accelerate contagion, enhancing infection rates especially when weak relationship infection rates are low. Conversely, in preferential and mixed structures, the influence of strong relationships is more subdued, with network architecture playing a more dominant role in contagion dynamics. Our results thus offer various hints for managing social contagion. For instance, enhancing positive interactions within specific network structures, such as increasing connectivity in preferential networks or stabilizing influential nodes in non-preferential networks, can significantly promote a rapid spread of positive information and healthy behaviors.