AQFC2015

On the Design and Analysis of Incentive Mechanisms in Social Systems

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                 Department of Systems Engineering and Engineering Management
                              The Chinese University of Hong Kong
 
 
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Date: Tuesday, November 4, 2014 - 11:00am - 12:30pm
 
Speaker: Dr. Yan CHEN, University of Maryland
 
Title: On the Design and Analysis of Incentive Mechanisms in Social Systems
 
Abstract:
With the rapid development of communication, computing and signal processing technologies, the last decade has witnessed a proliferation of social networks and systems that help to promote the connectivity of people to an unprecedentedly high level. Examples of these social systems can be found in a wide range of domains, from online social networks like Facebook or Twitter to crowdsourcing sites like Amazon Mechanical Turk or Topcoder where people solve various tasks by assigning them to a large pool of online workers; to online question and answering (Q&A) sites like Quora or Stack Overflow where people ask all kinds of questions.
Different from traditional networks and systems where uses are mandated by fixed and predetermined rules, users in these social systems have the ability to make intelligent decisions and their interactions are self-enforcing. Therefore, to achieve better system-wide performance, it is important to design effective incentive mechanisms to stimulate desired user behaviors. In this talk, we will discuss two of our recent works on the design and analysis of incentive mechanisms in social systems. First, we will discuss the quality control problem for microtask crowdsourcing from the perspective of incentives. After analyzing two widely adopted incentive mechanisms and showing their limitations, we propose a cost-effective incentive mechanism that can be employed to obtain high quality solutions from self-interested workers and ensure the budget constraint of requesters at the same time. Then, we will investigate the social computing systems where the value is created by voluntary user contributions and understanding how user participate is of key importance. We develop a game-theoretic framework to formally analyze the sequential decision makings of strategic users under the presence of complex externality. It is shown that our analysis is consistent with observations made from real-word user behavior data and can be applied to guide the design of incentive mechanisms in practice.
 
Biography:
Yan Chen is a founding member and principal technologist of Origin Wireless Communications Inc., and an affiliated research scientist in the Department of Electrical and Computer Engineering at University of Maryland working with Prof. K. J. Ray Liu. He received the Bachelor's degree from University of Science and Technology of China (USTC) in 2004, the M.Phil degree from Hong Kong University of Science and Technology (HKUST) in 2007, and the Ph.D. degree from University of Maryland College Park in 2011. His current research interests are in data science, network science, game theory, social learning and networking, as well as signal processing and wireless communications. He is the recipient of multiple honors and awards including best paper award from IEEE GLOBECOM in 2013, Future Faculty Fellowship and Distinguished Dissertation Fellowship Honorable Mention from Department of Electrical and Computer Engineering in 2010 and 2011, respectively, Finalist of Deans Doctoral Research Award from A. James Clark School of Engineering at the University of Maryland in 2011, and Chinese Government Award for outstanding students abroad in 2011. He has published more than 90 papers in prestigious international journals and conferences.
 
Everyone is welcome to attend the talk!
 
Venue: Room 513, William M.W. Mong Engineering Building (ERB), The Chinese University of Hong Kong.
 
The talk will be hosted by:
Prof. Helen Meng,
Department of Systems Engineering and Engineering Management,
The Chinese University of Hong Kong,
 
SEEM-5201 Website: http://seminar.se.cuhk.edu.hk
 
Date: 
Tuesday, November 4, 2014 - 03:00 to 04:30