Reputation-based Incentive Mechanisms in Crowdsourcing

RUI Lanlan; ZHANG Pan; HUANG Haoqiu; QIU Xuesong

doi:10.11999/JEIT151095

Volume 38 Issue 7

Jul. 2016

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RUI Lanlan, ZHANG Pan, HUANG Haoqiu, QIU Xuesong. Reputation-based Incentive Mechanisms in Crowdsourcing[J]. Journal of Electronics & Information Technology, 2016, 38(7): 1808-1815. doi: 10.11999/JEIT151095

Citation:

RUI Lanlan, ZHANG Pan, HUANG Haoqiu, QIU Xuesong. Reputation-based Incentive Mechanisms in Crowdsourcing[J]. Journal of Electronics & Information Technology, 2016, 38(7): 1808-1815. doi: 10.11999/JEIT151095

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Reputation-based Incentive Mechanisms in Crowdsourcing

doi: 10.11999/JEIT151095

Funds:

The National Natural Science Foundation of China (61302078, 61372108), The Funds for Creative Research Groups of China (61121061), Beijing Higher Education Young Elite Teacher Project (YETP0476)

Received Date: 2015-09-25
Rev Recd Date: 2016-04-22
Publish Date: 2016-07-19

Abstract

Abstract

Crowdsourcing is a new distributed problem solving pattern brought by the Internet. However, intrinsic incentive problems reside in crowdsourcing applications as workers and requester are selfish and aim to maximize their own benefit. In this paper, the following key contributions are made. A reputation-based incentive model is designed using repeated game theory, based on thorough analysis for current research on reputation and incentive mechanism; and a punishment mechanism is established to counter selfish workers. The experiment results show that the new established model can efficiently motivate the rational workers and counter the selfish ones. By setting punishment parameters appropriately, the overall performance of crowdsourcing system can be improved up to 90%, even if the fraction of selfish workers is 20%.
- Crowdsourcing system,
- Incentive mechanisms,
- Punishment mechanisms,
- Repeated game

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References(20)

References

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