In psychology and sociology, a trust metric is a measurement or metric of the degree to which one social actor (an individual or a group) trusts another social actor. Trust metrics may be abstracted in a manner that can be implemented on computers, making them of interest for the study and engineering of virtual communities, such as Friendster and LiveJournal.

Trust escapes a simple measurement because its meaning is too subjective for universally reliable metrics, and the fact that it is a mental process, unavailable to instruments. There is a strong argument against the use of simplistic metrics to measure trust due to the complexity of the process and the 'embeddedness' of trust that makes it impossible to isolate trust from related factors.

There is no generally agreed set of properties that make a particular trust metric better than others, as each metric is designed to serve different purposes, e.g. provides certain classification scheme for trust metrics. Two groups of trust metrics can be identified:

• Empirical metrics focusing on supporting the capture of values of trust in a reliable and standardized way;
• Formal metrics that focus on formalization leading to the ease of manipulation, processing and reasoning about trust. Formal metrics can be further classified depending on their properties.

Trust metrics enable trust modelling and reasoning about trust. They are closely related to reputation systems. Simple forms of binary trust metrics can be found e.g. in PGP. The first commercial forms of trust metrics in computer software were in applications like eBay's Feedback Rating. Slashdot introduced its notion of karma, earned for activities perceived to promote group effectiveness, an approach that has been very influential in later virtual communities.