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Reputation & Trust
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Denis GilletAdrian Holzer
“what is generally said or believed about a person’s or thing’s character.”
Reputation
“the extent to which one is willing to depend on another in a situation with a feeling of security, even in the face of possible negative consequences.”
TRUST
How is trustworthiness measured?
Trust in physical world
Derived from
personal experience
Influenced by received referrals from others
Trust related information
shared within local
communities
Trust in online environments Real-life evidences of trust are missing
Need adequate
electronic substitutes
for traditional cues
Trust related information shared on a global scale
A reputation score is associated with an item
The score is calculated by aggregation of all people’s trust opinions
The score is visible to the entire community
The score represents the trustworthiness
Examples
The reputation system incites sellers to be honest
Buyers use sellers’ reputation scores to assess the quality of sellers’ service
Sellers gain reputation when receiving positive ratings
Buyers provide a rating score to sellers
Rank reviewers (Advisor, Top Reviewer, Category Lead) Trust network (trust/distrust a person)
a professional community for eGovernment, eInclusion, eHealth
(L. Page, “The PageRank Citation Ranking: Bringing Order to the Web”, Technical Report, 1998)
Define different contexts
Specify a user’s reputation score depending on a
particular context
A user’s reputation score in Computer Science is high
Her reputation score in Chemistry is low
with current systems
Problems
Raters don’t directly benefit from rating items
Low incentive for providing rating
!
People hope to get a positive rating in return
Positive rating bias
!
Some people provide unfair ratings due to personal reasons
Unfair ratings
People with low reputation scores change their identities and enter the community as newcomers
Change of identities
POSSIBLE SOLUTIONS
Bias toward positive ratingsAllow anonymous ratings
Give extremely low reputation score to newcomers
Effective incentive mechanisms are needed
Exclude or give low weight to presumed unfair ratings, using statistical analysis
Low incentive for providing rating
Unfair ratings
Change of identities