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Political Science
Public Policy

A Framework for Policy Crowdsourcing - Oxford IPP 2014

Profile image of Araz 𝖳aeihaghAraz 𝖳aeihagh

IPP 2014 - Crowdsourcing for Politics and Policy

Abstract

Can Crowdsourcing be used for policy? Previous work posits that the three types of Crowdsourcing have different levels of potential usefulness when applied to the various stages of the policy cycle. In this paper, we build upon this exploratory work by categorizing the extant research with respect to Crowdsourcing for the policy cycle. Premised upon our analysis, we thereafter discuss the trends, highlight the gaps, and suggest some approaches to empirically validate the application of Crowdsourcing to the policy cycle.

FAQs

sparkles

AI

What explains the dominance of Open Collaboration in policy Crowdsourcing research?add

The study finds that Open Collaboration applications represent the majority of research efforts in policy Crowdsourcing, reflecting their suitability for public engagement and transparency. This observation indicates a substantial gap in investigating other Crowdsourcing types, such as VLMs and TBCs.

How does task magnitude differ across Crowdsourcing types?add

The research categorizes VLMs as eliciting microtasks, TBCs as yielding complete solutions, and Open Collaboration as variably spanning both spectrum extremes. Task magnitude significantly influences organizational strategy in selecting appropriate Crowdsourcing methods.

Why are VLMs underexplored in policy Crowdsourcing literature?add

The literature reveals VLMs are scarcely represented, possibly due to ethical concerns or policymakers' unfamiliarity. This lack of exploration presents untapped opportunities for researching VLM applications in policy contexts.

What unique insights arise from combining Crowdsourcing with the policy cycle?add

The paper synthesizes Crowdsourcing techniques with the policy cycle stages, identifying significant research gaps and overlaps. This framework aids in structuring future exploratory research in the burgeoning area of policy Crowdsourcing.

When did the research on policy Crowdsourcing begin to gain traction?add

Research into policy Crowdsourcing began to emerge prominently within the last five years, indicating growing academic and practical interest. Most studies are notably recent, suggesting rapid advancement in understanding its implications.

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References (64)

  1. AFUAH, A. & TUCCI, C. L. (2012) Crowdsourcing as a solution to distant search. Academy of Management Review. 37(3). p.355-375.
  2. AITAMURTO, T. (2012) Crowdsourcing for Democracy: A New Era in Policy-Making. Publication of the Committee for the Future Parliament of Finland. ISBN, 978-951.
  3. BALAGAPO, J. SAIBDONG, J. & Caro, J. (2014) Data crowdsourcing and traffic sensitive routing for a mixed mode public transit system. Information, Intelligence, Systems and Applications, IISA 2014, The 5th International Conference. IEEE.
  4. BASTO, D., FLAVIN, T., & PATINO, C (2010). Crowdsourcing Public Policy Innovation. Working Paper. Heinz College Carnegie Mellon University.
  5. BAYUS, B.L. (2012) Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community. Management Science, 59(1), p. 226-244.
  6. BENKLER, Y., ROBERTS, H., FARIS, R., SOLOW-NIEDERMAN, A. & Etling, B. (2013) Social Mobilization and the Networked Public Sphere: Mapping the SOPA-PIPA Debate. Berkman Center Research Publication No. 2013-16.
  7. BEN TAIEB, S. & HYNDMAN, R. J. (2013) A gradient boosting approach to the Kaggle load forecasting competition. International Journal of Forecasting. 30(2). p.382-394.
  8. BICQUELET, A. & WEALE, A. (2011) Coping with the Cornucopia: Can Text Mining Help Handle the Data Deluge in Public Policy Analysis? Policy & Internet. 3(4). Article 5.
  9. BOTT, M. & YOUNG, G. (2012) The Role of Crowdsourcing for Better Governance in International Development. Praxis: The Fletcher Journal of Human Security, 27. p.47-70.
  10. BRABHAM, D. C. (2008) Crowdsourcing as a model for problem solving an introduction and cases. Convergence. 14(1). p.75-90.
  11. BRABHAM, D. C. (2012). The effectiveness of crowdsourcing public participation in a planning context. First Monday. 17(12). p.307-328.
  12. BRABHAM, D. C. (2012b) Motivations for participation in a crowdsourcing application to improve public engagement in transit planning. Journal of Applied Communication Research. 40(3). p.307- 328. BRABHAM, D. C. (2013) The Four Urban Governance Problem Types Suitable for Crowdsourcing Citizen Participation. In C. SILVA (Ed.), Citizen E-Participation in Urban Governance: Crowdsourcing and Collaborative Creativity (pp. 50-68). Hershey, PA: Information Science Reference.
  13. BRABHAM, D. C. (2013a) Crowdsourcing. Cambridge, Massachusetts ; London, England: The MIT Press.
  14. BRABHAM, D. C. (2013b) Using Crowdsourcing In Government. IBM Center for The Business of Government.http://www.businessofgovernment.org/sites/default/files/Using%20Crowdsourcing %20In%20Government.pdf
  15. BRIDGMAN, P. & DAVIS, G. (2004). The Australian policy handbook. Allen & Unwin.
  16. BUA, A. (2012) Agenda setting and democratic innovation: The case of the Sustainable Communities Act (2007). Politics. 32(1). p.10-20.
  17. CHARALABIDIS, Y., TRIANTAFILLOU, A., KARKALETSIS, V., & LOUKIS, E. (2012) Public Policy Formulation through Non Moderated Crowdsourcing in Social Media. In Electronic Participation (pp. 156-169). Springer Berlin Heidelberg.
  18. CHUN, S. A. & CHO, J. S. (2012) E-participation and transparent policy decision making. Information Polity. 17(2). p. 129-145.
  19. DE VREEDE, T., NGUYEN, C., DE VREEDE, G. J., BOUGHZALA, I., Oh, O., & REITER-PALMON, R.
  20. A Theoretical Model of User Engagement in Crowdsourcing. In Collaboration and Technology (pp. 94-109). Springer Berlin Heidelberg.
  21. EASTON, D. (1979) A systems analysis of political life. Wiley, New York.
  22. ESTRELLES-AROLAS, E., & GONZALEZ-LADRON-DE-GUEVARA, F. (2012) Towards an integrated crowdsourcing definition. Journal of Information Science. 38(2). p.189-200.
  23. FERRO, E., LOUKIS, E. N., CHARALABIDIS, Y., & Osella, M. (2013) Policy making 2.0: From theory to practice. Government Information Quarterly. 30(4). p.359-368.
  24. FLICK, U. (2002) An Introduction to Qualitative Research. Sage: London.
  25. FRANKLIN, A., MOTT, T. & WILLIAMS, T.H. (2013) Coproduction in the US Department of Defense: Examining How the Evolution of Geographic Information Systems (GIS) Expands Non-Traditional Partner Engagement. Policy & Internet. 5(4). p.387-401.
  26. GHAFELE, R., GIBERT, B. & DiGIAMMARINO, P. (2011) Crowdsourcing patent application review to capitalize on innovation (No. 38330). University Library of Munich, Germany.
  27. HAKLAY, M., ANTONIOU, V., BASIOUKA, S., SODEN, R. & Mooney, P. (2014) Crowdsourced geographic information use in government, Report to GFDRR (World Bank). London HAYEK, F. A. (1945) The Use of Knowledge in Society. The American Economic Review. 35(4). p. 519-530 HOWE, J. (2006) Crowdsourcing: Crowdsourcing: A Definition. Crowdsourcing.com. Retrieved May 30, 2014, from http://crowdsourcing.typepad.com/cs/2006/06/crowdsourcing_a.html HOWE, J. (2008) Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business. Crown Business. Retrieved from http://www.bizbriefings.com/Samples/IntInst%20--- %20Crowdsourcing.PDF
  28. HOWLETT, M., RAMESH, M. & PERL, A. (1995) Studying public policy: Policy cycles and policy subsystems. (Vol. 163). Toronto: Oxford University Press.
  29. IPEIROTIS, P.G. & PARITOSH, P.K. (2011) Managing Crowdsourced Human Computation: A Tutorial. In Proceedings of the 20th international Conference Companion on World Wide Web. ACM. p.287-288.
  30. IRION, K. (2012) Government Cloud Computing and National Data Sovereignty. Policy & Internet. 4(3-4). p.40-71.
  31. JACKSON P. & KLOBAS, J. (2013) Deciding to use an enterprise wiki: the role of social institutions and scripts. Knowledge Management Research & Practice, 11(4). p.323-333.
  32. JENKINS, W. (1978) Policy Analysis: A Political and Organizational Perspective. New York, St. Martin's Press.
  33. JUNGHERR, A. JURGENS, P. (2010) The Political Click: Political Participation through E-Petitions in Germany. Policy & Internet. 2(4). p.131-165.
  34. KIETZMANN, J. H., HERMKENS, K., McCARTHY, I. P. & SILVESTRE, B.S. (2011) Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons. 54(3). p.241-251.
  35. KIM A. E., LIEBERMAN, A. J. & DENCH, D. (2014) Crowdsourcing Data Collection of the Retail Tobacco Environment: Case Study Comparing Data from Crowdsourced Workers to Trained Data Collectors. Tobacco control. tobaccocontrol-2013.
  36. KINGDON, J. W. & THURBER, J.A. (1984) Agendas, alternatives, and public policies (Vol. 45). Boston: Little, Brown.
  37. LASSWELL, H.D. (1956) The Decision Process: Seven Categories of Functional Analysis. Bureau of Governmental Research, College of Business and Public Administration, University of Maryland.
  38. LEEMAN, J, MYERS, A.E., RIBISL, K.M. & AMMERMAN, A.S. (2014) Disseminating Policy and Environmental Change Interventions: Insights from Obesity Prevention and Tobacco Control. International Journal of Behavioral Medicine. p.1-11.
  39. LINDNER, R. & RIEHM U. (2011) Broadening Participation Through E-Petitions? An Empirical Study of Petitions to the German Parliament. Policy & Internet. 3(1). Article 4.
  40. MICHELUCCI, P. (2013) Handbook of Human Computation. Springer New York.
  41. MILES, M. & HUBERMAN, A.M. (1994) Qualitative Data Analysis. Sage: Thousand Oaks, CA.
  42. NARULA, P., GUTHEIM P., ROLNITZKY, D., KULKARNI, A. & Hartmann, B. (2011) MobileWorks: A Mobile Crowdsourcing Platform for Workers at the Bottom of the Pyramid. In Proceedings of HCOMP.
  43. NASH, A. (2009) Web 2.0 Applications for Improving Public Participation in Transport Planning. In Transportation Research Board 89th Annual Meeting.
  44. NOVECK, B.S. (2009) Wiki-Government. How Technology Can Make Government Better, Democracy Stronger, and Citizens More Powerful. Washington, DC: Brookings Institution.
  45. MORGAN, J. & WANG, R. (2010) Tournaments for Ideas. California Management Review. 52(2), p.77-97.
  46. PALMER, B. (1997) Beyond Program Performance Indicators: Performance Information in a National System of Health and Family Services. Department of Health and Family Services. Canberra.
  47. PANANGIOTOPOULOUS, P., BIGDELI, A.Z. & Sams, S. (2014) Citizen-Government Collaboration on Social Media: The Case of Twitter in the 2011 Riots in England. Government Information Quarterly.
  48. PRIEUR, D. CARDON, J. BEAUCART, S. PISSARD, N. & PONS, P. (2008) The Strength of Weak Cooperation: A Case Study on Flickr. p. 610-613. Retrieved from http://arxiv.org/abs/0802.2317
  49. PRPIĆ , J. & SHUKLA, P. (2013) The Theory of Crowd Capital. Proceedings of the 46th Annual Hawaii International Conference on System Sciences. , Maui, Hawaii, January 7-10, Computer Society Press, 2013.
  50. PRPIĆ J., & SHUKLA, P. (2014) The Contours of Crowd Capability. Proceedings of the 47th Annual Hawaii International Conference on System Sciences. Big Island Hawaii, January 6-9, Computer Society Press, 2014.
  51. PRPIĆ, J., TAEIHAGH, A. & MELTON, J. (2014) Crowdsourcing the Policy Cycle. Collective Intelligence 2014. MIT Center for Collective Intelligence.
  52. PRPIĆ, J., JACKSON, P. & NGUYEN, T. (2014) A Computational Model of Crowds for Collective Intelligence. Collective Intelligence 2014. MIT Center for Collective Intelligence.
  53. PRPIĆ, J., SHUKLA, P., KIETZMANN, J.H. & McCarthy, I.P. (2015) How to Work a Crowd: Developing Crowd Capital Through Crowdsourcing. Business Horizons, Forthcoming.
  54. ROTH, Y. & Kimani, R. (2014) Crowdsourcing in the Production of Video Advertising: The Emerging Roles of Crowdsourcing Platforms. In R. J. DeFillippi & P. Wikström (Eds.), International Perspectives on Business Innovation and Disruption in the Creative Industries: Film, Video, Photography (pp. 1-36). Edward Elgar Publishing Ltd.
  55. SAWHNEY, M., Prandelli, E. & Verona, G. (2003) The Power of Innomediation. MIT Sloan Management Review, 44(2). p.77-82.
  56. SCHINTLER, L.A. & KULKARNI, R. (2014) Big Data for Policy Analysis: The Good, The Bad, and The Ugly. Review of Policy Research. 31(4). p.343-348.
  57. SELTZER, E. & MAHMOUDI, D. (2013) Citizen Participation, Open Innovation, and Crowdsourcing Challenges and Opportunities for Planning. Journal of Planning Literature. 28(1). p.3-18.
  58. STONE, D. A. (1988) Policy Paradox and Political Reason. Harper Collins.
  59. SUTTON, J., SPIRO, E.S., FITZHUGH, B.J., GIBSON, B. & BUTTS., C.T. (2014) Terse Message Amplification in the Boston Bombing Response. Proceedings of the 11th International ISCRAM Conference -University Park, Pennsylvania, USA, May 2014.
  60. STONE, D. A. (2002) Policy Paradox: The Art of Political Decision Making. W. W. Norton & Company Ltd, New York.
  61. STOTTLEMYRE, S. & STOTTLEMYRE, S. (2012). Crisis Mapping Intelligence Information During the Libyan Civil War: An Exploratory Case Study. Policy & Internet. 4(3-4). p.24-39.
  62. SUROWIECKI, J. (2005) The Wisdom of Crowds. Anchor Books.
  63. TROCHIM, W. M. (2005) Research Methods: The Concise Knowledge Base. Atomic Dog Publishing.
  64. YIN, R. (2009) Case Study Research: Design and Methods. 5th Ed. Thousand Oaks: Sage.

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