TAILIEUCHUNG - Building Web Reputation Systems- P14

Building Web Reputation Systems- P14:Today’s Web is the product of over a billion hands and minds. Around the clock and around the globe, people are pumping out contributions small and large: full-length features on Vimeo, video shorts on YouTube, comments on Blogger, discussions on Yahoo! Groups, and tagged-and-titled bookmarks. User-generated content and robust crowd participation have become the hallmarks of Web . | Help system display giving unknown users extra navigation help Lockout ofpotentially abused features such as content editing until the user has demonstrated familiarity with the application and lack of hostility to it Deciding when to route new contributions to customer care for moderation Pros Allows for a significantly lower barrier for some user contributions than otherwise possible for example not requiring registration or login. Provides for corporate internal use karma. No user knows this score and the site operator can change the application s calculation method freely as the situation evolves and new proxy reputations become available. Helps render your application impervious to accidental damage caused by drive-by users. Cons Inferred karma is by construction unreliable. For example since people can share an IP address over time without knowing it or each other including it in a reputation can undervalue an otherwise excellent user by accident. However though it might be tempting for that reason to remove IP reputation from the model IP address is the strongest indicator of bad users such users don t usually go to the trouble of getting a new IP address whenever they want to attack your site. Inferred karma can be expensive to generate. How often do you want to update the supporting reputations such as IP or cookie reputation It would be too expensive to update them at very single HTTP roundtrip so smart design is required. Inferred karma is weak. Don t trust it alone for any legally or socially significant actions. Practitioner s Tips Negative Public Karma Because an underlying karma score is a number product managers often misunderstand the interaction between numerical values and online identity. The thinking goes something like this In our application context the user s value will be represented by a single karma which is a numerical value. There are good trustworthy users and bad untrustworthy users and everyone would like to know which is which so we