A graphical representation of the SwiftRiver content rating system
In our latest post, we argued that a social network is NOT a wise crowd unless it comprises an efficient method to rate information and information sources in order to select good from bad user generated content. Well, it seems to be a hot topics: after Pachube, Ushahidi staff too is receiving comments on the difficulty of filtering bad (user generated) information from good one during a SwiftRiver deployment. This time, the staff replies with a rather technical post, explaining and graphically describing how users and content are validated by other users, with a redundancy that is hard to bypass, even for organized groups.
What would be absolutely possible is for a group to download Swift, set up their own instance with all sorts of fake information and publicize it as fact. However, our distributed, decentralized reputation system River ID would show that outside of that instances ‘ecosystem’ no one trusts those users, or the instance.
The post, with its nice – but rather obscure – pictures can be read here. A simpler explanation from another Ushahidi staff can be found here.