陈艳姣教授关于crowdsourcing的学术报告

日期:2016-09-26 | 学术活动 - 学术会议

Date:26/09/2016

Venue:meeting room 938

Presenter:  Dr. Chen(陈艳姣)

TopicIncentive Mechanism for Crowdsourcing


Biography:

  Dr. Chen received her B.E.degree in Electronic Engineering from Tsinghua University in July 2010 and her Ph.D. degree in Computer Science and Engineering from Hong Kong University of Science and Technology in January 2015. During May 2015 to April 2016, Dr. Chen has been working as a postdoctoral fellow at the University of Toronto. She has joined the Department of Computer Science, Wuhan University as a Professor in May 2016. Dr. Chen’s research interests include network economics, wireless and mobile networks, crowdsourcing, cloud computing. She has published many high-quality papers in IEEE Surveys and Tutorials, IEEE TMC, IEEE TWC, IEEE TPDS, and IEEE INFOCOM. Dr. Chen now serves as the executive editor of Transactions on Emerging Telecommunications Technologies (ETT), Wiley. She has received the New Star Award from ACM-Wuhan in 2016.


Abstract:

        Crowdsourcing provides an open, voluntary, and reliable environment for crowdsourcers and individuals to cooperate in achieving a cumulative result. In a crowdsourcing system, a proper incentive mechanism is essential for crowdsourcers to solicit high-quality work and sizeable participation of crowd workers. In this talk, we will introduce the state-of-art incentive mechanism design for crowdsourcing systems. We observe that with mobile social networking,a user enjoys an intrinsic benefit, which can be leveraged to complement extrinsic rewards provided by crowdsourcers. Referred to as network effects, such an intrinsic benefit becomes more significant as more users join and contribute to the crowdsourcing system.  We propose to incorporate network effects as a contributing factor to intrinsic rewards, and study its influence on the design of extrinsic rewards. We show that with our new incentive mechanism design, a crowdsourcer is able to attract more participants with higher contributed efforts; and the participants gain higher utilities from both intrinsic and extrinsic rewards.


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