Digital Trust
The digital trust models that we’re used to all involve Alice trusting Bob and Bob trusting Tom, resulting in Alice trusting Tom to some degree based on a formula. In other words, I trust someone, they trust someone else, therefore I trust the stranger. This model of trust is fairly intuitive.
What actually happened on the Internet is something completely different. People may not trust a stranger, but they seem to trust a mob of strangers. Take eBay as the example. I routinely send my money to someone I don’t know in hopes that they will send me something that looks like what they told me it would. I trust that they will for two reasons. First, their feedback rating tells me that they have done this in the past. Second, we both know that if they don’t, I will leave negative feedback and adversely affect their future business. This trust takes a while to build and is fragile. One negative can impact sales by an average of 14%, as well as spark the begin of a decline that might only be solved by an identity-change. [1]
Another good example of a Mob Trust (TM) model is Amazon’s (www.amazon.com review system. Again, I may not trust one person’s opinion of a book, but when 100 people dislike the book, I’m more likely to listen.
A third example is the Internet Movie Database www.imdb.com rating system. One can compare the top 100 rated movies from IMDB with the top 100 from the American Film Institute. The AFI list is restricted to American-made films, which leaves out such strong performers as Kirosawa’s Ran. The IMDB seems heavily influenced by the technical-lean of most of its contributors; the Lord of the Rings ranks fairly high.