Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms
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.
Keywords
Cite
@article{arxiv.1904.06722,
title = {Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms},
author = {Snehalkumar and S. Gaikwad and Durim Morina and Adam Ginzberg and Catherine Mullings and Shirish Goyal and Dilrukshi Gamage and Christopher Diemert and Mathias Burton and Sharon Zhou and Mark Whiting and Karolina Ziulkoski and Alipta Ballav and Aaron Gilbee and Senadhipathige S. Niranga and Vibhor Sehgal and Jasmine Lin and Leonardy Kristianto and Angela Richmond-Fuller and Jeff Regino and Nalin Chhibber and Dinesh Majeti and Sachin Sharma and Kamila Mananova and Dinesh Dhakal and William Dai and Victoria Purynova and Samarth Sandeep and Varshine Chandrakanthan and Tejas Sarma and Sekandar Matin and Ahmed Nasser and Rohit Nistala and Alexander Stolzoff and Kristy Milland and Vinayak Mathur and Rajan Vaish and Michael S. Bernstein},
journal= {arXiv preprint arXiv:1904.06722},
year = {2019}
}