English

Message-Passing Methods for Complex Contagions

Physics and Society 2024-01-31 v1 Social and Information Networks Dynamical Systems Probability Adaptation and Self-Organizing Systems

Abstract

Message-passing methods provide a powerful approach for calculating the expected size of cascades either on random networks (e.g., drawn from a configuration-model ensemble or its generalizations) asymptotically as the number NN of nodes becomes infinite or on specific finite-size networks. We review the message-passing approach and show how to derive it for configuration-model networks using the methods of (Dhar et al., 1997) and (Gleeson, 2008). Using this approach, we explain for such networks how to determine an analytical expression for a "cascade condition", which determines whether a global cascade will occur. We extend this approach to the message-passing methods for specific finite-size networks (Shrestha and Moore, 2014; Lokhov et al., 2015), and we derive a generalized cascade condition. Throughout this chapter, we illustrate these ideas using the Watts threshold model.

Cite

@article{arxiv.1703.08046,
  title  = {Message-Passing Methods for Complex Contagions},
  author = {James P. Gleeson and Mason A. Porter},
  journal= {arXiv preprint arXiv:1703.08046},
  year   = {2024}
}

Comments

14 pages, 3 figures