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# Intuition

Baseline for trust

The core idea behind EigenTrust is that a person’s reputation is defined recursively by the people who trust that person, weighted by those people’s reputations.

As a baseline, you can trust your friends. This gives you a good starting point, but because each person only has so many friends, it’s too limited to make a reliable system for millions of users/peers in a network. As a next step, you can expand that by asking your friends who they trust, and weighing their opinions by how much you trust your friends.

The linear algebra behind EigenTrust — you can initialize a trust vector with a set of seed peers that you trust. And then you can keep multiplying that vector by a matrix that represents the pairwise trust judgments of all the peers in the network. This is a power method algorithm, and it converges to the principal eigenvector of the matrix. Eventually you get complete coverage over everyone connected to you, directly or indirectly - in just a single eigenvector calculation.

Last modified 7mo ago