TAILIEUCHUNG - Building Web Reputation Systems- P20

Building Web Reputation Systems- P20: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 . | Some community members would report abuse for altruistic reasons out of a desire to keep the community clean. See the section Altruistic or sharing incentives on page 113. Downplaying the contributions of such users would be critical the more public their deeds became the less likely they would continue acting out of sheer altruism. Some community members had egocentric motivations for reporting abuse. The team appealed to those motivations by giving those users an increasingly greater voice in the community. The High-Level Project Model The team devised this plan for the new model a reputation model would sit between the two existing systems a report mechanism that permitted any user on Yahoo Answers to flag any other user s contribution and the human customer care system that acted on those reports. See Figure 10-3. This approach was based on two insights 1. Customer care could be removed from the loop in most cases by shifting the content removal process into the application and giving it to the users who were already the source of the abuse reports and then optimizing it to cut the amount of time and offensive posting by 90 . 2. Customer care could then handle just the exceptions undoing the removal of content mistakenly identified as abusive. At the time such false positives made up 10 of all content removal. Even if the exception rate stayed the same customer care costs would decrease by 90 . The team would accomplish item 1 removing customer care from the loop by implementing a new way to remove content from the site hiding. Hiding involved trusting the community members themselves to vote to hide the abusive content. The reputation platform would manage the details of the voting mechanism and any related karma. Because this design required no external authority to remove abusive content from view it was probably the fastest way to cut display time for abusive content. As for item 2 dealing with exceptions the team devised an ingenious mechanism an appeals

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