Goal
To provide a ‘network’ of peer review in order to calculate the credibility or authors and articles based on the credibility and reliability of ones peers, without comprosing personal scoring information of users
Terms
- user: someone participating in the project
- review (score/text): the review of an article or author in the form of a score and/or text
- reviewer: a user who reviews articles or authors
- credibility (score): the indication of how credible someones ‘reviews’ are.
- reliability (score): the indication of how reliable someones reliability or credibility scoring is.
- review directory: any site listing reviews by reviewers
Structure
a user stores the following under his site(a webhosting place under his control, a blog for instance):
- any review he has made on any author or article
- a ‘static’ table with the reliability score of his ‘peers’ (anyone he wants to score)
- a ‘cache’ with the reliability scores of ones peers peers.
- a ‘static’ table with the credibility score of his ‘peers’ (anyone he wants to score)
- a ‘cache’ with the credibility scores of ones peers peers.
user needs to be able to answer the following questions:
(no question can result in another request and ‘I do not know’ is a very valid answer)
what is your ‘review’ on an author/article
- If you do not know any thin about the author/article, you should answer ‘i do not know’.
- If you have made a review of the author/article you provide your review data.
How reliable do you think a user is
This result is computed as follows:
- You take the scores of your peers from the user
- each score is scaled down with the ‘relability of the peer’
example:
you take the score of user A from peer 1.
peer 1 has assigned a reliability of 70% to user A
you have a reliability of 60% assigned to peer 1
now the reliability of user A @ peer 1 is 60% of 70% == 42%
- you add your own score to the list
- you return the average scores of the list
- if neither you nor your peers have any scores of the user, you answer that you have no scores.
How credible do you think a user is.
This result is computed as follows:
- You take the credibility scores of your peers
- Each credibility score is scaled down with the ‘relability of the peer’
example:
you take the credibility score of user B from peer 2
peer 2 has assigned a credibility of 80% to user B
you have a reliability of 70% assigned to peer 2
now the credibility of user B at peer 2 if 70% of 80% == 56%
- you add your own score to the list
- your return the average score of the list
- if neither you nor your peers have any scores of the user, you answer that you have no scores.
Cache maintance
- Caches needed to be updated frequently but can -NEVER- be request based. This in order to prevent network loops.
- Caches are updated by asking questions from peers.
Directory maintanance
- users push reviews to directory sites.
- directory sites should demand authentication (for instance through openid) or do source checking.
- directiry sites are recommended to not pre-filter reviews
Filtering/Score checking
Credibility Score requesting by users
or: How to find out the credibility of an author or artcicle
- Lookup the author/article at a directory service and/or your peers.
- take the reviewer and request the score of the reviewer at your peers.
Filtering
- request an article list at an directory service
- take the score (see above) of each reviewer
- filter out all articles with score below oyour personally chosen threshold
