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Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms

Author

Listed:
  • Snehalkumar

    (Neil)

  • S. Gaikwad
  • Durim Morina
  • Adam Ginzberg
  • Catherine Mullings
  • Shirish Goyal
  • Dilrukshi Gamage
  • Christopher Diemert
  • Mathias Burton
  • Sharon Zhou
  • Mark Whiting
  • Karolina Ziulkoski
  • Alipta Ballav
  • Aaron Gilbee
  • Senadhipathige S. Niranga
  • Vibhor Sehgal
  • Jasmine Lin
  • Leonardy Kristianto
  • Angela Richmond-Fuller
  • Jeff Regino
  • Nalin Chhibber
  • Dinesh Majeti
  • Sachin Sharma
  • Kamila Mananova
  • Dinesh Dhakal
  • William Dai
  • Victoria Purynova
  • Samarth Sandeep
  • Varshine Chandrakanthan
  • Tejas Sarma
  • Sekandar Matin
  • Ahmed Nasser
  • Rohit Nistala
  • Alexander Stolzoff
  • Kristy Milland
  • Vinayak Mathur
  • Rajan Vaish
  • Michael S. Bernstein

Abstract

Paid crowdsourcing platforms suffer from low-quality work and unfair rejections, but paradoxically, most workers and requesters have high reputation scores. These inflated scores, which make high-quality work and workers difficult to find, stem from social pressure to avoid giving negative feedback. We introduce Boomerang, a reputation system for crowdsourcing that elicits more accurate feedback by rebounding the consequences of feedback directly back onto the person who gave it. With Boomerang, requesters find that their highly-rated workers gain earliest access to their future tasks, and workers find tasks from their highly-rated requesters at the top of their task feed. Field experiments verify that Boomerang causes both workers and requesters to provide feedback that is more closely aligned with their private opinions. Inspired by a game-theoretic notion of incentive-compatibility, Boomerang opens opportunities for interaction design to incentivize honest reporting over strategic dishonesty.

Suggested Citation

  • Snehalkumar & S. Gaikwad & Durim Morina & Adam Ginzberg & Catherine Mullings & Shirish Goyal & Dilrukshi Gamage & Christopher Diemert & Mathias Burton & Sharon Zhou & Mark Whiting & Karolina Ziulkoski, 2019. "Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms," Papers 1904.06722, arXiv.org.
    • Handle: RePEc:arx:papers:1904.06722
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    References listed on IDEAS

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    1. Nisan,Noam & Roughgarden,Tim & Tardos,Eva & Vazirani,Vijay V. (ed.), 2007. "Algorithmic Game Theory," Cambridge Books, Cambridge University Press, number 9780521872829, January.
    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    3. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, vol. 97(1), pages 242-259, March.
    4. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    5. Unknown, 2005. "Internet Advertising and the Generalized Second Price Auction: Selling Billions of Dollars Worth of Keywords," Department of Economics, Working Paper Series qt8w16v26k, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
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