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 Welcome to TrustLet, a cooperative environment for the scientific research of trust metrics on social networks. This is the wiki, where we review and understand trust and its related issues. You can also find more information about research on trust metrics, and the researchers involved in this. We mostly use the Creative Commons Attribution license. We also work on Python code, available under the GNU General Public License, to compare all proposed trust metrics on the same datasets. See Science Commons for more information about our mode of research..

Currently we are working on articles. See the guide for a deep description of the software.



A simple trust network
 digraph G { rankdir=LR; Alice -> Carol [label="       0.1        "]; ME -> Alice [label=" 0.85 "]; Bob -> Carol [label="       0.95        "]; ME -> Bob [label=" 0.7 "]; ME -> Carol [color=red,style=bold,label="?"]; { rank = same; "Bob"; "ME"; } { rank = same; "Alice"; "Carol"; } } User ME trusts user Alice as 0.85 (in [0,1]) and user Bob as 0.7. Alice trusts Carol as 0.1. Bob trusts Carol as 0.95. ME does not know Carol, so a trust metric can be used to predict how much Me could trust Carol. {| style="width:300px; margin:0 0 0 18px; padding:0px;" border="0"
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trust metrics

 * algorithms
 * evaluations
 * applications
 * software


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research

 * papers
 * working papers
 * researchers
 * conferences


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trust network datasets

 * repositories elsewhere
 * network file formats
 * visualizations


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trust

 * trustee
 * truster
 * related projects


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