Supersink Appleseed a Ziegler and Lausen, 2004 Based on spreading activation models Trust is modeled as energy Source node is activated through an injection of energy e is then propagated to other nodes along edges All energy is fully divided among successor nodes wrt their local edge weight. Supposing average out degrees >=1, the closer the sink is to the source, and the more paths leading from the source to the sink, the higher energy flowing to sink a Output: ranking of nodes
6 11/39 A B 9 3 A- A+ B- B+ A- A+ B- B+ Supersink 8 1 2 1 12/39 Appleseed Ziegler and Lausen, 2004 Based on spreading activation models Trust is modeled as energy Source node is activated through an injection of energy e e is then propagated to other nodes along edges All energy is fully divided among successor nodes wrt. their local edge weight. Supposing average out degrees >= 1, the closer the sink is to the source, and the more paths leading from the source to the sink, the higher energy flowing to sink Output: ranking of nodes
Tidaltrust and mole trust If the source does not know the sink the source asks all of its friends how much to trust the sink and computes a trust value by a weighted average Neighbors repeat the process if they do not have a direct rating for the sink tinty j∈ad()|t≥max j∈ad(j)|t≥maa so ource
7 13/39 TidalTrust and MoleTrust If the source does not know the sink, the source asks all of its friends how much to trust the sink, and computes a trust value by a weighted average Neighbors repeat the process if they do not have a direct rating for the sink 14/39 Source Sink