Toward collective intelligence of online communities: A primitive conceptual model

Shuangling Luo , Haoxiang Xia , Taketoshi Yoshida , Zhongtuo Wang

Journal of Systems Science and Systems Engineering ›› 2009, Vol. 18 ›› Issue (2) : 203 -221.

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Journal of Systems Science and Systems Engineering ›› 2009, Vol. 18 ›› Issue (2) : 203 -221. DOI: 10.1007/s11518-009-5095-0
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Toward collective intelligence of online communities: A primitive conceptual model

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Abstract

Inspired by the ideas of Swarm Intelligence and the “global brain”, a concept of “community intelligence” is suggested in the present paper, reflecting that some “intelligent” features may emerge in a Web-mediated online community from interactions and knowledge-transmissions between the community members. This possible research field of community intelligence is then examined under the backgrounds of “community” and “intelligence” researches. Furthermore, a conceptual model of community intelligence is developed from two views. From the structural view, the community intelligent system is modeled as a knowledge supernetwork that is comprised of triple interwoven networks of the media network, the human network, and the knowledge network. Furthermore, based on a dyad of knowledge in two forms of “knowing” and “knoware”, the dynamic view describes the basic mechanics of the formation and evolution of “community intelligence”. A few relevant research issues are shortly discussed on the basis of the proposed conceptual model.

Keywords

Community intelligence / online community / knowledge supernetwork / knowing / knoware

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Shuangling Luo, Haoxiang Xia, Taketoshi Yoshida, Zhongtuo Wang. Toward collective intelligence of online communities: A primitive conceptual model. Journal of Systems Science and Systems Engineering, 2009, 18(2): 203-221 DOI:10.1007/s11518-009-5095-0

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References

[1]

Argyris C., Schon D.A.. Organizational Learning, 1978, Reading MA: Addison-Wesley

[2]

Akgüna A.E., Dayanb M., Benedettoc A.D.. New product development team intelligence: antecedents and consequences. Information & Management, 2008, 45(4): 221-226.

[3]

Balis M.E., Krakoff I.H., Berman P.H., Dancis J.. Urinary metabolites in congenital hyperuricosuria. Science, 1967, 156(3778): 1123.

[4]

Bonabeau E., Dorigo M., Theraulaz G.. Swarm Intelligence: from Natural to Artificial Systems, 1999, New York: Oxford University Press, OUP USA Inc..

[5]

Brown P., Lauder H.. Baron S., Field J., Schuller T.. Collective Intelligence. Social Capital: Critical Perspectives, 2000, New York: Oxford University Press 230

[6]

Cannon-Bowers J.A., Salas E., Converse S.. Castellan N.J. Jr.. Shared mental models in expert team decision making. Individual and Group decision Making: Current issues, 1993, Hillsdale, NJ: LEA 221-246.

[7]

Cook S.D., Brown J.S.. Bridging epistemologies: the generative dance between organizational knowledge and organizational knowing. Organization Science, 1999, 10(4): 381-400.

[8]

Cowan R., Jonard N.. Network structure and the difusion of knowledge. Journal of Economic Dynamics and Control, 2004, 28(8): 1557-1575.

[9]

Epstein J.. Agent-based computational models and generative social science. Complexity, 1999, 4(5): 41-60.

[10]

Eppler M.J., Burkard R.A.. Knowledge visualization: towards a new discipline and its fields of application. ICA Working Paper #2/2004, 2004, Lugano: University of Lugano

[11]

Fischer G.. Bjornestad S.. Communities of Interest: learning through the interaction of multiple knowledge systems. Proceedings of the 24th Information Systems Research Seminar in Scandinavia, 2001, Bergen: Department of Information Science, University of Bergen

[12]

Gabelnick F., MacGregor J., Matthews R.S., Smith B.L.. Learning Communities: Creating Connections among Students, Faculty, and Disciplines, 1990, Jossey-Bass: John Wiley & Sons, Inc.

[13]

Girvan M., Newman M.E.J.. Community structure in social and biological networks. Proceedings of National Academy of Sciences, 2002, 99(12): 7821-7826.

[14]

Heylighen, F. (2005). Conceptions of a global brain: an historical review. Available via DIALOG. http://pespmc1.vub.ac.be/Papers/GBconceptions.pdf. Cited 2005

[15]

Hjorland B.. Fundamentals of knowledge organization. Knowledge Organization, 2003, 30(2): 87-111.

[16]

Johnson, N., Rasmussen, S., Joslyn, C., Rocha, L., Smith, S. & Kantor, M. (1998). Symbiotic intelligence: self-organizing knowledge on distributed networks driven by human interactions. In: Adami, C. et al. (eds.), 6th Artificial Life Conference’ 98, MIT Press

[17]

Johnson-Laird P.N.. Norman D.A.. Mental models in cognitive science. Perspectives on Cognitive Science, 1981, Norwood, NJ: Ablex 147-191.

[18]

Kennedy J., Eberhart R.. Swarm Intelligence, 2001, San Francisco: Morgan Kaufmann

[19]

Klimoski R., Mohammed S.. Team mental model: construct or metaphor?. Journal of Management, 1994, 20(2): 403-437.

[20]

Lave J., Wenger E.. Situated Learning: Legitimate Peripheral Participation, 1991, Cambridge, UK: University of Cambridge Press

[21]

Levy, P. (1994). Collective Intelligence: Mankind’s Emerging World in Cyberspace. Basic Books

[22]

Luhn, H.P. (1958). A business intelligence system. IBM Journal, October, 314–319

[23]

Marshall S.P.. Schemas in Problem Solving, 1995, Cambridge, UK: University of Cambridge Press

[24]

Mayer-Kress G., Barczys C.. The global brain as an emergent structure from the Worldwide computing network, and its implications for modeling. The Information Society, 1995, 11(1): 1-27.

[25]

MIT Center for Collective Intelligence (2008). In: Handbook of collective intelligence. Available via DIALOG. http://scripts.mit.edu/~cci/HCI/index.php Cited Nov 18th, 2008

[26]

Nagurney, A. & Wakolbinger, T. (2005). Supernetworks: An introduction to the concept and its applications with a specific focus on knowledge supernetworks. International Journal of Knowledge, Culture and Change Management, 4

[27]

Nonaka I.. A dynamic theory of organizational knowledge creation. Organization Science, 1994, 5(1): 14-37.

[28]

O’Reilly, T. (2005). What is Web 2.0: design patterns and business models for the next generation of software. Available via DIALOG. http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html. Cited 2005

[29]

Porter C.E.. A typology of virtual communities: a multi-disciplinary foundation for future research. Journal of Computer-mediated Communication, 2004, 10(1): 3

[30]

Rheingold H.. The Virtual Community: Homesteading on the Electronic Frontier, 2000, London: MIT Press

[31]

Russell P.. The Global Brain: Speculations on the Evolutionary Leap to Planetary Consciousness, 1983, Boston, MA: Houghton Mifflin

[32]

Segaran, T. (2007). Programming Collective Intelligence: Building Smart Web 2.0 Applications. O’Reilly Press

[33]

Scardamalia M., Bereiter C.. Computer support for knowledge-building communities. Journal of the Learning Sciences, 1994, 3(3): 265-283.

[34]

Szuba T.. Computational Collective Intelligence, 2001, New York: Wiley

[35]

Tönnies F.. Loomis P.C.. Gemeinschaft und Gesellschaft, 1887, Leipzig: Fues’s Verlag

[36]

Wang F., Carley K., Zeng D., Mao W.. Social computing: from social informatics to social intelligence. IEEE Intelligent Systems, 2007, 22(2): 79-83.

[37]

Weick K.E., Roberts K.H.. Collective mind in organizations: heedful interrelating on flight decks. Administrative Science Quarterly, 1993, 38: 357-381.

[38]

Wellman B., Wortley S.. Different strokes from different folks: community ties and social support. American Journal of Sociology, 1990, 96(3): 558-588.

[39]

Wierzbicki A.P., Nakamori Y.. Creative Space: Models of Creative Processes for the Knowledge Civilization Age, 2005, Berlin: Springer

[40]

Zhong N., Liu J.M., Yao Y.Y.. Web Intelligence, 2003, Berlin: Springer.

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