skip to main content
10.1145/1978942.1979148acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
research-article

Human computation: a survey and taxonomy of a growing field

Published:07 May 2011Publication History

ABSTRACT

The rapid growth of human computation within research and industry has produced many novel ideas aimed at organizing web users to do great things. However, the growth is not adequately supported by a framework with which to understand each new system in the context of the old. We classify human computation systems to help identify parallels between different systems and reveal "holes" in the existing work as opportunities for new research. Since human computation is often confused with "crowdsourcing" and other terms, we explore the position of human computation with respect to these related topics.

References

  1. Ask 500 People. http://www.ask500people.com.Google ScholarGoogle Scholar
  2. Bederson, B. B., Hu, C., & Resnik, P. Translation by iterative collaboration between monolingual users.GI'10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Bernstein, M., Miller, R. C., Little, G., Ackerman, M., Hartmann, B., Karger, D. R., & Panovich, K. Soylent: A Word Processor with a Crowd Inside. Proc. UIST 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Biewald, L. Massive multiplayer human computation for fun, money, and survival. XRDS (Dec. 2010), 10--15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Bigham, J. P., Jayant, C., Ji, H., Little, G., Miller, A., Miller, R. C., Miller, R., Tatrowicz, A., White, B., White, S., & Yeh, T. VizWiz: nearly real-time answers to visual questions. UIST 2010, ACM (2010), 333--342. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Callison-Burch, C., & Dredze, M. Creating Speech and Language Data with Amazon's Mechanical Turk. Workshop on Creating Speech And Language Data With Amazon's Mechanical Turk NAACL HLT, (2010), 1--12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. ChaCha search engine. http://www.chacha.com.Google ScholarGoogle Scholar
  8. Chan, K. T., King, I., & Yuen, M. Mathematical modeling of social games. Proc CSE 2009, 1205--1210. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Chandrasekar, R., Chi, E., Chickering, M., Ipeirotis, P. G., Mason, W., Provost, F., Tam, J., von Ahn, Front matter. Proc. SIGKDD HCOMP 2010.Google ScholarGoogle Scholar
  10. Chen, K., Wu, C., Chang, Y., & Lei, C. A crowdsourceable QoE evaluation framework for multimedia content. Proc MM 2009, ACM, 491--500. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Chklovski, T. Learner: a system for acquiring commonsense knowledge by analogy. Proc. K-CAP '03. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Chklovski, T. Collecting paraphrase corpora from volunteer contributors. Proc. K-CAP'05, ACM (2005). Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Chklovski, T. & Gil, Y. Towards Managing Knowledge Collection from Volunteer Contributors, KCVC 2005.Google ScholarGoogle Scholar
  14. Cooper, S., Khatib, F., Treuille, A., Barbero, J., Lee, J., Beenen, M., Leaver-Fay, A., Baker, D., & Popovic, Z. Predicting protein structures with a multiplayer online game. Nature, 466:7307, (Aug. 2010), 756--760.Google ScholarGoogle ScholarCross RefCross Ref
  15. Dryer, D. C., Eisbach, C., & Ark, W. S. At what cost pervasive? a social computing view of mobile computing systems. IBM Systems Journal, (Dec 1999). Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Edmunds, P. SwarmSketch. http://swarmsketch.com/.Google ScholarGoogle Scholar
  17. Fayyad, U., Piatetsky-Shapiro, P., & Smyth, P. Knowledge Discovery and Data Mining: Towards a Unifying Framework. Proc. KDD 1996.Google ScholarGoogle Scholar
  18. Gentry, C., Ramzan, Z., & Stubblebine, S. Secure distributed human computation. Proc EC 2005, 155--164. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Gonçalves, D., Jesus, R., & Correia, N. A gesture based game for image tagging. CHI 2008 EA.Google ScholarGoogle Scholar
  20. Help Find Jim. http://www.helpfindjim.com.Google ScholarGoogle Scholar
  21. Horvitz, E. & Paek, T. Complementary computing: policies for transferring callers from dialog systems to human receptionists. User Modeling and User-Adapted Interaction 17, 1-2 (Mar. 2007), 159--182. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Howe, Jeff. The Rise of Crowdsourcing. Wired. Jun'06.Google ScholarGoogle Scholar
  23. Howe, Jeff. Crowdsourcing: Why the Power of the Crowd is Driving the Future of Business. Crown (2008). Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Howe, Jeff. Crowdsourcing: A Definition. http://crowdsourcing.typepad.com.Google ScholarGoogle Scholar
  25. Hu, C., Bederson, B. B., & Resnik, P. MonoTrans2: A New Human Computation System to Support Monolingual Translation, Proc. CHI 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Iowa Electronic Markets. http://www.biz.uiowa.edu/iem.Google ScholarGoogle Scholar
  27. Ipeirotis, P. G. Analyzing the Amazon Mechanical Turk Marketplace. XRDS 17:2, ACM (Dec. 2010), 16--21. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Ipeirotis, P. G., Chandrasekar, R., & Bennett, P. Report on the human computation workshop. HCOMP 2010.Google ScholarGoogle Scholar
  29. Ipeirotis, P. G., Provost, F., & Wang, J. Quality management on Amazon Mechanical Turk. HCOMP'10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Kittur, A., Suh, B., Pendleton, B. A., & Chi, E. He says, she says:conflict and coordination in Wikipedia. CHI'07. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Koblin, A. Sheep Market. http://thesheepmarket.com.Google ScholarGoogle Scholar
  32. Kosorukoff, A. Human based genetic algorithm. Trans. on Systems, Man, and Cybernetics, 5:3464, IEEE (2001).Google ScholarGoogle Scholar
  33. Law, E. & von Ahn, L. Input-agreement: a new mechanism for collecting data using human computation games. Proc. CHI 2009, 1197--1206. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Law, E., West, K., Mandel, M., Bay, M., Downie, J. S. Evaluation of algorithms using games: the case of music tagging. Proc. ISMIR 2009, 387--392.Google ScholarGoogle Scholar
  35. Lenat, D. B. CYC: a large-scale investment in knowledge infrastructure, CACM, (Nov. 1995), 33--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Levy, P. Collective intelligence: Mankind's emerging world in cyberspace. Perseus, Cambridge, MA, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Licklider, J. C. R. Man-computer symbiosis. IRE Transactions on Human Factors in Electronics, vol. HFE-1 IEEE (Mar. 1960), 4--11.Google ScholarGoogle ScholarCross RefCross Ref
  38. Lieberman, H., Smith, D., & Teeters, A. Common Consensus: a web-based game for collecting common-sense goals. Proc. IUI 2007.Google ScholarGoogle Scholar
  39. Little, G., Chilton, L. B., Goldman, M., and Miller, R. C. Exploring iterative and parallel human computation processes. Proc. HCOMP 2010, 68--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. LiveOps. http://www.liveops.com.Google ScholarGoogle Scholar
  41. Malone, T. W., Laubacher, R., & Dellarocas, C. N. Harnessing crowds: Mapping the genome of collective intelligence. MIT Sloan Research Paper 4732-09, (2009).Google ScholarGoogle Scholar
  42. Mataric, M. J. Designing emergent behaviors: from local interactions to collective intelligence. Proc of Animals To Animats 2, MIT Press (1993), 432--441. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Mason, W. & Watts, D. J. Financial incentives and the "performance of crowds". SIGKDD Explorations Newsletter. 11:2, ACM (May 2010), 100--108. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Mechanical Turk. http://mturk.com.Google ScholarGoogle Scholar
  45. Nalimov, E. V., Wirth, C., & Haworth, G. M. KQQKQQ and the Kasparov-World Game. ICGA J., (1999)195--212.Google ScholarGoogle Scholar
  46. News Futures. http://www.newsfutures.com.Google ScholarGoogle Scholar
  47. Page, L., Brin, S., Motwani, R., & Winograd, T. The PageRank citation ranking: Bringing order to the Web. Tech. report, Stanford Digital Libraries Project (1998).Google ScholarGoogle Scholar
  48. Parameswaran, M. & Whinston, A. B. Social Computing: An Overview. CAIS 19:37, (2007), 762--780.Google ScholarGoogle Scholar
  49. Peha, J. M. & Khamitov, I. M. PayCash: a secure efficient Internet payment system. Proc. ICEC 2003, 125--130. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Quinn, A. & Bederson, B. B. A Taxonomy of Distributed Human Computation. Tech. Rep. HCIL-2009-23, University of Maryland, (2009).Google ScholarGoogle Scholar
  51. Quinn, A., Bederson, B. B., Yeh, T., & Lin, J. CrowdFlow: Integrating Machine Learning with Mechanical Turk for Speed-Cost-Quality Flexibility. Tech. Rep HCIL-2010-09, Univ. of Maryland, (2009).Google ScholarGoogle Scholar
  52. reCAPTCHA. http://recaptcha.net.Google ScholarGoogle Scholar
  53. Resnik, P., Buzek, O., Hu, C., Kronrod, Y., Quinn, A., & Bederson, B. B. Improving Translation via Targeted Paraphrasing, EMNLP 2010, ACL (2010), 127--137. Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. Schall, D., Truong, H., & Dustdar, S. The Human-Provided Services Framework. CECANDEEE 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Secretan, J., Beato, N., Ambrosio, D. D. B., & Rodriguez, A., Campbell, A., Stanley, K. O. Picbreeder: evolving pictures collaboratively online. Proc CHI 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Sheng, V., Provost, F., & Ipeirotis, P. Get Another Label? improving data quality and data mining using multiple nosy labelers. KDD 2008, 614--622. Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. Silberman, S. Inside the High Tech Hunt for a Missing Silicon Valley Legend. Wired Magazine. (Jul. 24, 2007). http://wired.com/techbiz/people/magazine/15-08/ff_jimgray.Google ScholarGoogle Scholar
  58. Singh, P., Lin, T., Mueller, E. T., Lim, G., Perkins, T., & Zhu, W. L. Open Mind Common Sense: Knowledge Acquisition from the General Public. Lecture Notes in Computer Science, v. 2519, Springer (2002), 1223--1237. Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. Surowiecki, J. The Wisdom of Crowds. Anchor (2005). Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. The FACTory. http://game.cyc.com.Google ScholarGoogle Scholar
  61. Tong, S. & Koller, D. Support vector machine active learning with applications to text classification. J. Mach. Learn. Res. 2 (Ma. 2002), 45--66. Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. Turing, A. M. Computing Machinery and Intelligence. Mind, 59:236, Oxford University Press (1950), 433--460.Google ScholarGoogle Scholar
  63. von Ahn, L. & Dabbish, L. Labeling images with a computer game. Proc CHI 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  64. von Ahn, L. Human Computation. Doctoral Thesis. UMI Order Number: AAI3205378, Carnegie Mellon University, (2005). Google ScholarGoogle ScholarDigital LibraryDigital Library
  65. von Ahn, L. Games with a Purpose. Computer, 39:6, IEEE Computer Society (Jun 2006), 92--96. Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. von Ahn, L. & Dabbish, L. Designing Games with a Purpose. CACM, 51:8, (Aug. 2008), 58--67. Google ScholarGoogle ScholarDigital LibraryDigital Library
  67. von Ahn, L., Kedia, M, & Blum, M. Verbosity: a game for collecting common-sense facts. Proc CHI 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. von Ahn, L., Maurer, B., McMillen, C., Abraham, D., & Blum, M. ReCAPTCHA: human-based character recognition via web security measures. Science, 321:5895, (Sept. 12, 2008), 1465--1468.Google ScholarGoogle ScholarCross RefCross Ref
  69. Wayland, F. The Limitations Of Human Responsibility. Applewood Books, Bedford, Massachusetts, (1838).Google ScholarGoogle Scholar
  70. Westphal, A. J., Butterworth, A. L., Snead, C. J., Craig, N., Anderson, D., Jones, S. M., Brownlee, D. E., Farnsworth, R., Zolensky, M. E. Stardust@ home: A Massively Distributed Public Search for Interstellar Dust in the Stardust Interstellar Dust Collector. Thirty-Sixth Lunar and Planetary Science Conference (2005).Google ScholarGoogle Scholar
  71. Wikipedia. http://en.wikipedia.org/wiki/Wikipedia:5P.Google ScholarGoogle Scholar
  72. Wolfers, J. & Zitzewitz, E. Prediction markets. Journal of Economic Perspectives, 18:2, (2004), 107--126.Google ScholarGoogle ScholarCross RefCross Ref
  73. Yang, Y., Zhu, B. B., Guo, R., Yang, L., Li, S., & Yu, N. A comprehensive human computation framework: with application to image labeling. Proc. MM 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. Yuen, M., Chen, L., & King, I. A Survey of Human Computation Systems. Proc CSE 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Human computation: a survey and taxonomy of a growing field
      Index terms have been assigned to the content through auto-classification.

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
        May 2011
        3530 pages
        ISBN:9781450302289
        DOI:10.1145/1978942

        Copyright © 2011 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 7 May 2011

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        CHI '11 Paper Acceptance Rate410of1,532submissions,27%Overall Acceptance Rate6,199of26,314submissions,24%

        Upcoming Conference

        CHI '24
        CHI Conference on Human Factors in Computing Systems
        May 11 - 16, 2024
        Honolulu , HI , USA

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader