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Re: exploring a crowdsourced certification trust metric with svg/javascript animation

From: Dan Brickley <danbri@danbri.org>
Date: Wed, 14 Apr 2010 17:54:11 +0200
Message-Id: <AD8DA2CE-3EC9-4E14-B2B5-A0365697B52A@danbri.org>
To: Dan Connolly <connolly@w3.org>
Cc: www-talk <www-talk@w3.org>

On 14 Apr 2010, at 17:09, Dan Connolly <connolly@w3.org> wrote:

> Some of us have been noodling around...
> Open User Community Development
> http://www.w3.org/2008/OUCD/wiki/Main_Page
> I found a python implementation of the advogato trust metric,
> but I'm struggling to get my head around it.
> So I wrote a little piece of code to simulate growth of
> a social network; people join, and they friend/follow/certify
> others with certain probabilities. Also, with some
> probability, they joined the network to exploit it
> rather than to contribute; i.e. they're evil.
> Evil folks sometimes certify other evil folks,
> but contributors know better. The python code writes
> out each step of the simulation in JSON.

I like this approach, and expect this data-driven exploration (even if  
simulated data) could help get reputation-based, distributed trust out  
of the eternal "someday pile".

However in everyday business, sheer unadulterated evil ( Spam, fraud  
etc ie. generally clear-cut mischief) is one huge problem amongst  
many. Mailing lists, blogs etc can also suffer from over-enthusiastic  
participants whose contributions aren't quite right (in volume, tone  
or theme) for that forum. I am curious how far into that space we can  
go, and whether a common design can handle the spam problem and also  
help with fuzzier questions of authority, trust and interestingness.  
How far do you see it going in that direction? Is this just for 'evil  
people', or also 'foolish actions'?


Received on Wednesday, 14 April 2010 15:54:45 UTC

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