| Abstract | | Existing computational trust systems analyze information
networks to determine the "trustworthiness" of the nodes, but the
scalar values they produce are both opaque and semantically
variable, and knowing only that the trustworthiness of a website is
"27" is not helpful to the user. Moreover, the simplistic
means by which they are typically calculated can yield misleading
results, sometimes dramatically so. We present a new,
standardized set of trust metrics that instead compute the
trustworthiness of an information source as a triple of
truthfulness, completeness, and bias scores, and argue that these
must be calculated relative to the user to be
meaningful. We then explore these new metrics with a user
study. |