Cs234r Markets for Networks and Crowds B RENDAN L UCIER, M ICROSOFT R ESEARCH NE N ICOLE I MMORLICA, M ICROSOFT R ESEARCH NE.

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cs234r Markets for Networks and Crowds B RENDAN L UCIER, M ICROSOFT R ESEARCH NE N ICOLE I MMORLICA, M ICROSOFT R ESEARCH NE

Lecture 6: Nicole Immorlica, Greg Stoddard, and Vasilis Syrgkanis. Social Status and Badge Design, International World Wide Web Conference, 2015.

CROWDSOURCING CONTENT:

VIRTUAL REWARDS – LEADERBOARD:

VIRTUAL REWARDS – BADGES:

Editing. Flagging. VIRTUAL REWARDS – BADGES:

THIS PAPER: 1.Propose model of user incentives. Users contribute to achieve social status. 2.Study the content generation of various reward schemes used in practice. Websites confer status by granting rewards like badges and leaderboards.

RESULTS: 1.For any status preferences, optimal design is a leaderboard with a contribution cutoff. 2.When status exhibits diminishing returns, a badge mechanism is approximately optimal. 3.When status exhibits increasing returns, a full leaderboard is approximately optimal.

USERS: abilities (drawn at random) contributions (chosen by user)

REWARD SCHEME: partition into status classes (based on contribution) first classlast class

USER BEHAVIOR: best classworst class

SITE DESIGNER:

EXAMPLES OF SCHEMES:

AUCTION CONNECTION: users: given ability choose contribution to max utility. (reward scheme) valuebid

designing reward mechanisms that maximize contributions designing all-pay auctions that maximize revenue (with feasibility constraints imposed by status)

OPTIMAL REWARD MECHANISM: Theorem: Leaderboard with a contribution cut-off (chosen based on ability distribution) is optimal and has a unique equilibrium. 1 st 2 nd 3 rd 4 th no reward

APPROXIMATE OPTIMALITY:

badge no reward

APPROXIMATE OPTIMALITY: 1 st 2 nd 3 rd 4 th last 5 th

INFORMAL discussion: Leaderboards w/cutoff optimal, hard to design/play. Badges are effective at incentivizing contributions for users with concave status concerns. Full leaderboards effective at incentivizing contributions for users with convex status concerns.