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Understanding Crowd-Powered Search Groups: A Social Network Perspective 1,2 1 1,3 4 Qingpeng Zhang *, Fei-Yue Wang , Daniel Zeng , Tao Wang 1The State Key Laboratory of Management and Control for Complex Systems, Chinese Academy of Sciences, Beijing, China, 2 Department of Systems and Industrial Engineering, The University of Arizona, Tucson, Arizona, United States of America, 3 Department of Management Information Systems, The University of Arizona, Tucson, Arizona, United States of America, 4 The Research Center for Computational Experiments and Parallel Systems, National University of Defense Technology, Changsha, Hunan, China Abstract Background: Crowd-powered search is a new form of search and problem solving scheme that involves collaboration among a potentially large number of voluntary Web users. Human flesh search (HFS), a particular form of crowd-powered search originated in China, has seen tremendous growth since its inception in 2001. HFS presents a valuable test-bed for scientists to validate existing and new theories in social computing, sociology, behavioral sciences, and so forth. Methodology: In this research, we construct an aggregated HFS group, consisting of the participants and their relationships in a comprehensive set of identified HFS episodes. We study the topological properties and the evolution of the aggregated network and different sub-groups in the network. We also identify the key HFS participants according to a variety of measures. Conclusions: We found that, as compared with other online social networks, HFS participant network shares the power-law degree distribution and small-world property, but with a looser and more distributed organizational structure, leading to the diversity, de