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[MIT] Online Reputation Systems: How to Design One That Does What You Need

There is a top-notch post on creating reputation systems over at the MIT Sloan Management Review: Online Reputation Systems: How to Design One That Does What You Need by Chrysanthos Dellarocas, an associate professor of management at Boston University School of Management and an affiliated researcher at MIT's Center for Collective Intelligence

It's fairly lengthy, and aligns very closely with what we cover in greater detail in our book. Here I've excerpted only the section headers to peak your interest. Go read it, bookmark it, and if you have an MIT Sloan account, please leave a comment. BTW, if anyone has the author's address, we'd love to send professor Dellarocas a free copy...

How can a website attract the contributors it needs?

  • Key Decision #1: What are the key business objectives of your reputation system?
    • Build Trust
    • Promote Quality
    • Facilitate Member Matching
    • Sustain Loyalty
  • Key decision #2: What information should be included in your user’s reputation profile?
    • Which actions are most relevant to the reputation system’s users?
    • Which user behaviors are desirable?
    • For which behaviors is it possible to obtain reliable information?
  • Key Decision #3: How should reputation information be aggregated and displayed?
    Reputation mechanisms employ a variety of methods for displaying outputs. These fall into three large categories:
    • Raw activity statistics. Examples: number of reviews posted, number of transactions completed.
    • Scores and distinctions. Examples: star ratings (such as Amazon reviews), numerical scores (eBay’s feedback score, TopCoder’s user rating), numbered levels or named member tiers (World of Warcraft’s player levels, Slashdot’s “moderator” and “meta-moderator” tiers) or achievement badges (eBay power seller, Amazon Top Reviewer).
    • Leaderboards and other methods of displaying relative user rankings. Examples: the list of top Amazon reviewers; Epinions’ author popularity ranking.


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