2025/11/19 by Keating, Leah A., Hébert-Dufresne, Laurent
Environmental Science · Physics and Astronomy · #Branching (polymer chemistry) #Branching process #Complex Network Analysis Techniques #Complex network #Ecosystem dynamics and resilience #FOS: Physical sciences #Group (periodic table) #Intersection (aeronautics) #Network structure #Opinion Dynamics and Social Influence #Phase transition #Physics and Society (physics.soc-ph) #Population #Process (computing)
paper · open access · doi:10.48550/arxiv.2511.15688
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2025/11/19 · openalex created_date 2025/11/23 · openalex updated_date 2026/07/28
We study a self-consistent approach to introduce higher-order effects in a branching process model of complex contagion on clustered networks. Branching processes operate over an infinite population such that they never circle back and interact with previously exposed parts of the system. This infinite, treelike, structure makes it tricky to account for complex contagion mechanisms such as group effects, peer pressure, or social reinforcement where multiple exposures interact in synergistic ways. Here we present a self-consistent solution that accounts for local group structure and global cycles where the process can feedback on itself. This allows us to distinguish multiple exposures that stem from a single transmission chain, from those occurring at the intersection of different transmission chains. We find that only the latter mechanism can give rise to a discontinuous phase transition in the size of global cascades, which is a defining feature of complex contagions. Group effects alone, without long cycles, produce standard continuous phase transitions.