Self-Reinforcing Cascades: A Spreading Model for Beliefs or Products of Varying Intensity or Quality

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.

Authors

Institutions

Publication Details

Journal
Physical Review Letters
Published
2025-07-18
DOI
https://doi.org/10.1103/5mph-sws5
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Self-Reinforcing Cascades: A Spreading Model for Beliefs or Products of Varying Intensity or Quality

S. Redner, Giulio Burgio, James P. Gleeson, P. L. Krapivsky et al.
Physical Review Letters
Opinion Dynamics and Social Influence
article

Self-Reinforcing Cascades: A Spreading Model for Beliefs or Products of Varying Intensity or Quality

S. Redner, Giulio Burgio, James P. Gleeson, P. L. Krapivsky, Juniper Lovato, Karl J. Friston
article en

Abstract

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.

Physical Review LettersVol. 135(8)
University of Vermont (US), Santa Fe Institute (US), University of Limerick (IE)
Openalex Percentile: Top 84%
Opinion Dynamics and Social Influence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Self-Reinforcing Cascades: A Spreading Model for Beliefs or Products of Varying Intensity or Quality — S. Redner, Giulio Burgio, et al. · Physical Review Letters (2025) | TGRS Research Map | TGRS