# Emergence of simple and complex contagion dynamics from weighted belief networks

arXiv: https://arxiv.org/abs/2301.02368 · HTML: https://mlsanity.com/paper/2301.02368/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jan 2023.

## Built on by (most cited first, 4 of 4)

- [A semantic embedding space based on large language models for modelling human beliefs](https://mlsanity.com/paper/2408.07237/) (2024)
- [Why Trust in AI May Be Inevitable](https://mlsanity.com/paper/2502.20701/) (2025)
- [SP-GCRL: Influence Maximization on Incomplete Social Graphs](https://mlsanity.com/paper/2605.12513/) (2026)
- [Coherence-Driven Belief Formation and Population Dynamics of Contagion in LLM Agents](https://mlsanity.com/paper/2610.02654/) (2026)

## Abstract (arXiv)

Social contagion is a ubiquitous and fundamental process that drives individual and social changes. Although social contagion arises as a result of cognitive processes and biases, the integration of cognitive mechanisms with the theory of social contagion remains an open challenge. In particular, studies on social phenomena usually assume contagion dynamics to be either simple or complex, rather than allowing it to emerge from cognitive mechanisms, despite empirical evidence indicating that a social system can exhibit a spectrum of contagion dynamics -- from simple to complex -- simultaneously. Here, we propose a model of interacting beliefs, from which both simple and complex contagion dynamics can organically arise. Our model also elucidates how a fundamental mechanism of complex contagion -- resistance -- can come about from cognitive mechanisms.