· On gnutella, did you know that you can watch what other people are searching for? The book has a screenshot of gnutella client v0.56, I have Gnucleus, but you can do it in Gnucleus by clicking Tools –> Statistics –> Log. Betcha you didn’t know that an entire company was founded based on that idea did you?
· On the ‘small-world’ model and the importance of bridges: “.. The key to understanding the result lies in the distribution of links within social networks. In any social grouping, some acquaintances will be relatively isolated and contribute few new contacts, whereas otherws will have more wide-ranging connections and be able to serve as bridges between far-flung social clusters. These bridging vertices play a critical role in bringing the network closer together… It turns out that the presence of even a small number of bridges can dramatically reduce the lengths of paths in a graph, …” — Reference “Collective dynamics of ‘small-world’ networks” published in Nature, download the PDF.
· Publius looks like some cool software
· Crowds: “Crowds is a system whose goals are similar to that of mix networks but whose implementation is quite different. Crowds is based on that idea that people can be anonymous when they blend into a crowd. As with mix networks, Crowds users need not trust a single third party in order to maintain their anonymity. A crowd consists of a group of web surfers all running the Crowds software. When one crowd member makes a URL request, the Crowds software on the corresponding computer randomly chooses between retrieving the requested document or forwarding the request to a randomly selected member of the crowd…. ” — Read more about Crowds at the official site.
· Tragedy of the Commons. This idea was mentioned in chapter 16 on Accountability and is talked about in various other books I’ve read, but I’m not sure that I ever recorded the source. The idea came from Garrett Hardin in a paper written in 1968 called “The Tragedy of the Commons”, which you can read on his site.
· On accountability and how we really *are* all just six degrees apart. Read the PGP Web of Trust statistics if you don’t believe it.
· On reputation systems, specifically Advogato’s Trust Metric
· On reputation scoring systems, a good system “… will possess many of the following qualities:
- Accurate for long-term performance: The system reflects the confidence (the likelihood of accuracy) of a given score. It can also distinguish between a new entity of unknown quality and an entity with bad long-term performance.
- Weighted toward current behavior: The system recognizes and reflects recent trends in entity performance. For instance, an entity that has behaved well for a long time but suddenly goes downhill is quickly recognized and no longer trusted.
- Efficient: It is convenient if the system can recalculate a score quickly. Calculations that can be performed incrementally are important.
- Robust against attacks: The system should resist attempts of any entity or entities to influence scores other than by being more honest or having higher quality.
- Amenable to statistical evaluation: It should be easy to find outliers and other factors that can make the system rate scores differently.
- Private: No one should be able to learn how a given rater rated an entity except the rater himself.
- Smooth: Adding any single rating or small number of ratings doesn’t jar the score much.
- Understandable: It should be easy to explanin to people who use these scores what they mean — not only so they know how the system works, but so they can evaluate for themselves what the score implies.
- Verifiable: A score under dispute can be supported with data.”
· On reputation scoring systems: “Vulnerabilities from overly simple scoring systems are not limited to “toy” systems like Instant Messenger. Indeed, eBay suffers from a similar problem. In eBay, the reputation score for an individual is a linear combination of good and bad ratings, one for each transaction. Thus, a vendor who has performed dozens of transactions and cheats on only 1 out of every 4 customers will have a steadily rising reputation, whereas a vendor who is completely honest but has done only 10 transactions will be displayed as less reputable. As we have seen, a vendor could make a good profit (and build a strong reputation!) by being honest for several small transactions and then being dishonest for a single large transaction.”
· The book was written when Reputation Technologies was still a distinct company, but I thought this list of Reputation and Asset Management vendors was interesting in that reputation is something that is becoming more and more important.. for instance, when was the last time you purchased something from eBay where the vendor had a bad rating? Never right? Did you ever stop to think about how the vendor in question got a bad rating? Since when is eBay a good judge of someone’s character? Why do we trust eBay’s reputation algorigthms?
· On the optimal size of an organization: “Business theorists have observed that the ability to communicate broadly and deeply through the Internet as low cost is driving a process whereby large businesses break up into a more competitive system of smaller component companies. They call this process ‘deconstruction.’ This process is an example of Coase’s Law, which states that other things being equal, the cost of a transaction — negotiating, paying, dealing with errors or fraud — between firms determines the optimal size of the firm. When business transactions between firms are expensive, it’s more economical to have larger firms, even though larger firms are considered less efficient because they are slower to make decisions. When transactions are cheaper, small firms can replace the larger integrated entity.”