Sam Scarpino (@scarpino.bsky.social)

Self-Reinforcing Cascades: A Spreading Model for Beliefs or Products of Varying Intensity or Quality Laurent Hébert-Dufresne, Juniper Lovato, Giulio Burgio, James P. Gleeson, S. Redner, and P. L. Krapivsky Phys. Rev. Lett. 135, 087401 Models of how things spread often assume that transmission mechanisms are fixed over time. However, social contagions—the spread of ideas, beliefs, innovations—can lose or gain in momentum as they spread: ideas can get reinforced, beliefs strengthened, products refined. We study the impacts of such self-reinforcement mechanisms in cascade dynamics. We use different mathematical modeling techniques to capture the recursive, yet changing nature of the process. We find a critical regime with a range of power-law cascade size distributions with nonuniversal scaling exponents. This regime clashes with classic models, where criticality requires fine-tuning at a precise critical point. Self-reinforced cascades produce critical-like behavior over a wide range of parameters, which may help explain the ubiquity of power-law distributions in empirical social data. Read the full article at: link.aps.org https://sco.lt/6HeQEq