Trust Network

A trust network is a special class of social network in which edges carry weights representing degrees of trust rather than mere connection. Unlike standard networks where edges are binary or weighted by interaction frequency, trust networks encode relational quality: the expectation that an interaction partner will act cooperatively rather than exploitatively. This makes trust networks the substrate on which social capital is built and on which systemic risk in social systems propagates.

The topology of trust networks differs systematically from generic social networks. They exhibit higher clustering coefficients because trust is transitive — if Alice trusts Bob and Bob trusts Carol, Alice is likely to trust Carol — producing dense local triangles. They also show stronger community structure because trust formation requires repeated interaction, and repeated interaction is easier within groups than across them. The weighted graph formalism from graph theory provides the mathematical language for trust networks, but the weights are not arbitrary: they encode the outcome history of the relationship and are therefore path-dependent in ways that standard weighted-graph models rarely capture.

The study of trust networks has been held back by importing network measures designed for communication or disease networks and applying them to trust without asking whether trust obeys the same topological laws. It does not. A trust network is not a network with trust on top; it is a fundamentally different topology generated by a different microdynamic.