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The Chinese “Human Flesh” Web: the first decade and beyond

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Chinese Science Bulletin

Abstract

Human flesh search (HFS), a Web-enabled crowdsourcing phenomenon, originated in China a decade ago. In this article, we present the first comprehensive empirical analysis of HFS, focusing on the scope of HFS activities, the patterns of HFS crowd collaboration process, and the characteristics of HFS participant networks. A survey of HFS participants was conducted to provide an in-depth understanding of the HFS community and various factors that motivate these participants to contribute. This article also advocates a new stream of Web science and social computing research that will be important in predicting the future growth and use of the World Wide Web.

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References

  1. Wang F-Y, Zeng D, Hendler JA et al (2010) A study of the human flesh search engine: crowd-powered expansion of online knowledge. Computer 43:45–53

    Article  Google Scholar 

  2. Howe J (2009) Crowdsourcing: why the power of the crowd is driving the future of business. Three Rivers Press, New York

    Google Scholar 

  3. Doan A, Ramakrishnan R, Halevy AY (2011) Crowdsourcing systems on the world-wide web. Commun ACM 54:86–96

    Article  Google Scholar 

  4. Kietzmann J, Angell I (2010) Panopticon revisited. Commun ACM 53:135–138

    Article  Google Scholar 

  5. Hellerstein JM, Tennenhouse DL (2011) Searching for Jim Gray: a technical overview. Commun ACM 54:77–87

    Article  Google Scholar 

  6. Palen L, Hiltz SR, Liu SB (2007) Online forums supporting grassroots participation in emergency preparedness and response. Commun ACM 50:54–58

    Article  Google Scholar 

  7. Wang B, Hou B, Yao Y et al (2009) Human flesh search model incorporating network expansion and GOSSIP with feedback. In: Turner SJ, Roberts D, Cai W (eds) IEEE/ACM International Symposium on Distributed Simulation and Real-Time Applications. 13th IEEE/ACM Symposium on Distributed Simulation and Real-Time Applications (DS-RT 2009), Singapore, October 2009. IEEE Computer Soc, DC, pp 82–88

  8. Ahn Y, Bagrow J, Lehmann S (2010) Link communities reveal multiscale complexity in networks. Nature 466:761–764

    Article  Google Scholar 

  9. Bonabeau E, Dorigo M, Theraulaz G (2000) Inspiration for optimization from social insect behaviour. Nature 406:39–42

    Article  Google Scholar 

  10. Hendler J, Shadbolt N, Hall W et al (2008) Web science: an interdisciplinary approach to understanding the web. Commun ACM 51:60–69

    Article  Google Scholar 

  11. Wang F-Y, Carley KM, Zeng D et al (2007) Social computing: from social informatics to social intelligence. IEEE Intell Syst 22:79–83

    Article  Google Scholar 

  12. Zeng D, Wang F-Y, Carley KM (2007) Guest editors’ introduction: social computing. IEEE Intell Syst 22:20–22

    Article  Google Scholar 

  13. Wang F-Y (2007) Toward a paradigm shift in social computing: the ACP approach. IEEE Intell Syst 22:65–67

    Article  Google Scholar 

  14. Barabási A (2009) Scale-free networks: a decade and beyond. Science 325:412–413

    Article  Google Scholar 

  15. Clauset A, Moore C, Newman M (2008) Hierarchical structure and the prediction of missing links in networks. Nature 453:98–101

    Article  Google Scholar 

  16. Zhang Q, Wang F-Y, Zeng D et al (2012) Understanding crowd-powered search groups: a social network perspective. PLoS One 7:e39749

    Article  Google Scholar 

  17. Broder A, Kumar R, Maghoul F et al (2000) Graph structure in the web. Comput Netw 33:309–320

    Article  Google Scholar 

  18. Glott R, Schmidt P, Ghosh R (2010) Wikipedia survey—overview of results. United Nations University: Collaborative Creativity Group

  19. Zhang Q (2012) Analyzing cyber-enabled social movement organizations: a case study with crowd-powered search. University of Arizona, Tuscan

    Google Scholar 

  20. Chen C, Wu K, Srinivasan V et al (2011) Battling the internet water army: detection of hidden paid posters. arXiv preprint arXiv:11114297

  21. Wang G, Wilson C, Zhao X et al (2012) Serf and turf: crowdturfing for fun and profit. In: Proceedings of the 21st international conference on World Wide Web. ACM, New York, pp 679–688

  22. Liang B, Lu H (2010) Internet development, censorship, and cyber crimes in China. J Contemp Crim Justice 26:103–120

    Article  Google Scholar 

  23. Eubank S, Guclu H, Anil Kumar VS et al (2004) Modelling disease outbreaks in realistic urban social networks. Nature 429:180–184

    Article  Google Scholar 

  24. Kleinberg J (2007) Computing: the wireless epidemic. Nature 449:287–288

    Article  Google Scholar 

  25. Gonzalez MC, Hidalgo CA, Barabasi AL (2008) Understanding individual human mobility patterns. Nature 453:779–782

    Article  Google Scholar 

  26. Song C, Koren T, Wang P et al (2010) Modelling the scaling properties of human mobility. Nat Phys 6:818–823

    Article  Google Scholar 

  27. Song C, Qu Z, Blumm N et al (2010) Limits of predictability in human mobility. Science 327:1018–1021

    Article  Google Scholar 

  28. Lazer D, Pentland A, Adamic L et al (2009) Computational social science. Science 323:721–723

    Article  Google Scholar 

  29. Watts DJ (2007) A twenty-first century science. Nature 445:489

    Article  Google Scholar 

  30. Pickard G, Pan W, Rahwan I et al (2011) Time-critical social mobilization. Science 334:509–512

    Article  Google Scholar 

  31. Chi EH (2009) Information seeking can be social. Computer 42:42–46

    Article  Google Scholar 

  32. Introne J, Laubacher R, Malone T (2011) Enabling open development methodologies in climate change assessment modeling. IEEE Softw 28:56–61

    Article  Google Scholar 

  33. Introne J, Laubacher R, Olson G et al (2011) The climate CoLab: large scale model-based collaborative planning. Collab Technol Syst 40–47

  34. Yu L, Nickerson J, Sakamoto Y (2012) Collective creativity: where we are and where we might go. Collect Intell (CI’12)

  35. Wang F-Y (2011) Study on cyber-enabled social movement organizations based on social computing and parallel systems. J Univ Shanghai Sci Technol 33:8–17 (in Chinese)

  36. Hendler J, Berners-Lee T (2010) From the semantic web to social machines: a research challenge for AI on the World Wide Web. Artif Intell 174:156–161

    Article  Google Scholar 

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Acknowledgement

The authors thank Guanpi Lai for his help in collecting data during this research. This work was supported in part by the National Natural Science Foundation of China (90924302, 91024030, 71025001, 70890084, and 60921061), the US Defense Advanced Research Projects through two seedling grants to Rensselaer Polytechnic Institute, and the US National Science Foundation support for EAGER (IIS-1143585).

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Fei-Yue Wang & Daniel Zeng

  2. Department of Management Information Systems, The University of Arizona, Tucson, Arizona, 85721, USA

    Daniel Zeng

  3. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China

    Qingpeng Zhang

  4. Tetherless World Constellation, Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA

    James A. Hendler

  5. The Research Center for Computational Experiments and Parallel Systems, National University of Defense Technology, Changsha, 410073, China

    Jianping Cao

Authors
  1. Fei-Yue Wang
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  2. Daniel Zeng
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  3. Qingpeng Zhang
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  4. James A. Hendler
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  5. Jianping Cao
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Corresponding author

Correspondence to Fei-Yue Wang.

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Wang, FY., Zeng, D., Zhang, Q. et al. The Chinese “Human Flesh” Web: the first decade and beyond. Chin. Sci. Bull. 59, 3352–3361 (2014). https://doi.org/10.1007/s11434-014-0480-6

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  • DOI: https://doi.org/10.1007/s11434-014-0480-6

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