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Trustlet, Open Research on Trust Metrics

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Paolo Massa
Paolo Massa

Presentation of a paper at 11th Business Information Systems conference - 2nd Workshop on Social Aspects of the Web (SAW 2008). Trustlet.org is a cooperative environment (wiki) for research of trust metrics on social networks, sharing of social network datasets and of trust metrics code as Free Software

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Trustlet, Open Research on Trust Metrics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],License: Creative Commons (see last slide for details)
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What is trust? ,[object Object],[object Object]
What is trust? ,[object Object],[object Object],[object Object],[object Object],[object Object]
What is trust? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Alice Bob 0.6
Trust on the Web: gimme examples! ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object]
[object Object],1 ,[object Object],[object Object],Alice Bob
[object Object],0.9 1 ,[object Object],[object Object],Properties of Trust: - weighted (0=distrust, 1=max trust) Alice Carol Bob
[object Object],0.9 1 ,[object Object],[object Object],Properties of Trust: - weighted (0=distrust, 1=max trust) - subjective Alice Carol Bob 0 Dave 0.6
[object Object],0.9 1 ,[object Object],[object Object],Properties of Trust: - weighted (0=distrust, 1=max trust) - subjective - asymmetric 0.2 Alice Carol Bob 0 Dave 0.6
[object Object],0.9 1 ,[object Object],[object Object],Properties of Trust: - weighted (0=distrust, 1=max trust) - subjective - asymmetric - context dependent 0.2 Alice Carol Bob 0 Dave 0.6
[object Object],0.9 1 0.2 Alice Carol Bob 0 Dave 0.6
[object Object],[object Object],[object Object],0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
Trust Metric! Uses existing edges 0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
Trust Metric! Uses existing edges for predicting values of trust for non-existing edges , 0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
Trust Metric! Uses existing edges for predicting values of trust for non-existing edges, thanks to trust propagation (if you trust someone, then you have some degree of trust in anyone that person trusts). 0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
Trust Metric! Uses existing edges for predicting values of trust for non-existing edges, thanks to trust propagation (if you trust someone, then you have some degree of trust in anyone that person trusts). Pagerank is a Trust Metric 0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
[object Object],[object Object],[object Object],0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
Local and Global Trust Metrics How much Dave can be trusted? - On average (by the community)? - By Alice? - And by ME? 1 1 0 ME Bob Carol 1 Alice Dave
Local and Global Trust Metrics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],How much Dave can be trusted? - On average (by the community)? - By Alice? - And by ME? 1 1 0 ME Bob Carol 1 Alice Dave
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Trust Metrics Research ,[object Object],[object Object],[object Object]
How many Trust Metrics? ,[object Object],[object Object],[object Object]
Trustlet.org: the wiki! ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
http://www.trustlet.org
Datasets @ Trustlet.org ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Trust Metrics Code @ Trustlet.org ,[object Object],[object Object],[object Object],[object Object],[object Object]
Empirical Comparison @ Trustlet.org ,[object Object],[object Object]
S tate of the Art @ Trustlet.org ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Initial results ,[object Object],[object Object]
Advogato trust network ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
Trust statements expressed by raph
Advogato trust network dataset ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Trust Metrics Evaluation ,[object Object],0.9 1 0.75 0.2 Alice Carol Bob 0 Dave 0.6
Trust Metrics Evaluation ,[object Object],0.9 1 0.75 0.2 X 1. Hide one trust statement real_trust(A,D)=0.75 Alice Carol Bob 0 Dave 0.6
Trust Metrics Evaluation ,[object Object],0.9 1 0.75 0.2 X T(A,D)=0.6 1. Hide one trust statement real_trust(A,D)=0.75 2. Predict it with a Trust Metric pred_trust(A,D)=0.6 Alice Carol Bob 0 Dave 0.6
Trust Metrics Evaluation ,[object Object],0.9 1 0.75 0.2 X T(A,D)=0.6 1. Hide one trust statement real_trust(A,D)=0.75 2. Predict it with a Trust Metric pred_trust(A,D)=0.6 3. Compute error as difference (or other measure) error(A,D)=|0.6-0.75|=0.15 Alice Carol Bob 0 Dave 0.6
Trust Metrics Evaluation ,[object Object],0.9 1 0.75 0.2 X 1. Hide one trust statement real_trust(A,D)=0.75 2. Predict it with a Trust Metric pred_trust(A,D)=0.6 3. Compute error as difference (or other measure) error(A,D)=|0.6-0.75|=0.15 4. Repeat the process for all trust statements and compute some mean error T(A,D)=0.6 Alice Carol Bob 0 Dave 0.6
Trust Metrics evaluation Measures ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Compared Trust Metrics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
MoleTrust: local propagation ME
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Trust metrics evaluated on all trust edges Compare Ebay and Moletrust2 on %wrong
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Trust metrics evaluated on all trust edges Compare Ebay and Moletrust2 on MAE
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Trust metrics evaluated on all trust edges Compare Ebay and Moletrust2 on RMSE
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Trust metrics evaluated on all trust edges Compare Ebay and Moletrust2 on RMSE ,[object Object],[object Object]
Uhm ... ,[object Object],[object Object],[object Object],[object Object]
TM evaluated on trust edges to controversial users ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],AlwaysMaster predicts always 5 as trust score
TM evaluated on trust edges to controversial users ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],AlwaysMaster seems the best one for %wrong and very bad for RMSE! Results depending on evaluation measure?!?
TM evaluated on trust edges to controversial users ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],OutA predicts avg of trust outgoing from source user A
TM evaluated on trust edges to controversial users ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],OutA is best for RMSE! Reason: ”observer” has a different semantics. Difficult to evaluate!
Eventually ...
TM evaluated on trust edges to controversial users ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Ebay (global) and Moletrust2 (local) similar also on controversial users!
TM evaluated on trust edges to controversial users ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Ebay (global) and Moletrust2 (local) similar also on controversial users! Different from Epinions! No need for local trust metrics?!? Evaluation method not appropriate?!? Characteristics of the community?
Ongoing work ,[object Object],[object Object]
Join the collaborative effort at trustlet.org! ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you! ,[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Trustlet, Open Research on Trust Metrics

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  • 15. Trust Metric! Uses existing edges 0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
  • 16. Trust Metric! Uses existing edges for predicting values of trust for non-existing edges , 0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
  • 17. Trust Metric! Uses existing edges for predicting values of trust for non-existing edges, thanks to trust propagation (if you trust someone, then you have some degree of trust in anyone that person trusts). 0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
  • 18. Trust Metric! Uses existing edges for predicting values of trust for non-existing edges, thanks to trust propagation (if you trust someone, then you have some degree of trust in anyone that person trusts). Pagerank is a Trust Metric 0.9 1 ? 0.2 Alice Carol Bob 0 Dave 0.6
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  • 20. Local and Global Trust Metrics How much Dave can be trusted? - On average (by the community)? - By Alice? - And by ME? 1 1 0 ME Bob Carol 1 Alice Dave
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