Understanding the wikipedia phenomenon: a case for agent based modeling

ABSTRACT

Wikipedia, the user led and monitored "open" encyclopedia has been an undoubted popular success. Of particular interest are the diffusion process of the innovation throughout the "contributor" community, and the question as to why unpaid, often well qualified, volunteers contribute content and time. Explanations for 'altruistic' contributor behavior based on the positivistic paradigm, and with roots in organizational psychology, while heavily researched and documented, have not been readily transferable to quantitative models of sufficient predictive value, in relation to Wikipedia's metrics. For despite the wide range of types, ages, locations and motivations of its contributors and seekers, investigators on Wikipedia have identified certain definite and often surprisingly universal trends ('laws') in its overall growth curve, organization structure, community and article formation. Models based on aggregated top-level relationships between entities on and around wikipedia suffer from assuming relationships between these entities as inputs to the wikipedia process, rather than emergent phenomena that evolve and change with the output. We argue for an Agent Based Model of Wikipedia, with the end objective of our work being a tool with diagnostic and/or prescriptive value for decision makers in organizations using or planning to use Knowledge Management Systems.

REFERENCES

• 1: M. Quaddus, J. Xu, Adoption and diffusion of knowledge management systems: field studies of factors and variables, Knowledge-Based SystemsVolume 18, Issues 2-3, April 2005, Pages 107--115.
• 2: E. M. Rogers, Diffusion of Innovations, fourth ed., The Free Press, 1995.
• 3: V. L. Saga , R. W. Zmud, The Nature and Determinants of IT Acceptance, Routinization, and Infusion, Proceedings of the IFIP TC8 Working Conference on Diffusion, Transfer and Implementation of Information Technology, p.67-86, October 11-13, 1993
• 4: R. Agarwal, J. Prasad, The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies, Decision Sciences 28 (3) (1997) 557--582.
• 5: Felipe Ortega , Jesus M. Gonzalez Barahona, Quantitative analysis of thewikipedia community of users, Proceedings of the 2007 international symposium on Wikis, p.75-86, October 21-25, 2007, Montreal, Quebec, Canada [doi>10.1145/1296951.1296960]
• 6: WikipediaStats:http://en.wikipedia.org/wiki/Wikipedia%3ASize_comparisons
• 7: T. Chesney. An empirical examination of Wikipedias credibility. First Monday, 11(11), 2006.
• 8: A. Capocci, et al. Preferential attachment in the growth of social networks: the case of wikipedia (2006). URL http://arxiv.org/abs/physics/0602026. physics/0602026.
• 9: Dennis M. Wilkinson , Bernardo A. Huberman, Cooperation and quality in wikipedia, Proceedings of the 2007 international symposium on Wikis, p.157-164, October 21-25, 2007, Montreal, Quebec, Canada [doi>10.1145/1296951.1296968]
• 10: Aniket Kittur , Bongwon Suh , Bryan A. Pendleton , Ed H. Chi, He says, she says: conflict and coordination in Wikipedia, Proceedings of the SIGCHI conference on Human factors in computing systems, April 28-May 03, 2007, San Jose, California, USA [doi>10.1145/1240624.1240698]
• 11: A. Kittur, E. Chi, B. A. Pendleton, B. Suh, and T. Mytkowicz. Power of the few vs. wisdom of the crowd: Wikipedia and the rise of the bourgeoisie. Proceedings of the 25th Annual ACM Conference on Human Factors in Computing Systems (CHI 2007), April-May 2007.
• 12: D. Anthony, S. W. Smith, and T. Williamson. Explaining quality in internet collective goods: Zealots and good samaritans. The case of wikipedia. November 2005.
• 13: J. Voss. Measuring wikipedia. Proceedings of the ISSI 2005, July 2005.
• 14: L. S. Buriol, C. Castillo, D. Donato, S. Leonardi, and
• 15: Luciana S. Buriol , Carlos Castillo , Debora Donato , Stefano Leonardi , Stefano Millozzi, Temporal Analysis of the Wikigraph, Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence, p.45-51, December 18-22, 2006 [doi>10.1109/WI.2006.164]
• 16: Cliff Lampe , Paul Resnick, Slash(dot) and burn: distributed moderation in a large online conversation space, Proceedings of the SIGCHI conference on Human factors in computing systems, p.543-550, April 24-29, 2004, Vienna, Austria [doi>10.1145/985692.985761]
• 17: Oded Nov, What motivates Wikipedians?, Communications of the ACM, v.50 n.11, p.60-64, November 2007 [doi>10.1145/1297797.1297798]
• 18: D. Cohen and L. Prusak, In Good Company: How Social Capital Makes Organizations Work, Harvard Business School Press, Boston, MA, 2001. 224 pp. (ISBN 087584913X)
• 19: D Bandura, A. (Ed.) (1995), Self-efficacy in changing societies. New York: Cambridge University
• 20: McElroy, M. W. (2000), "Integrating complexity theory, knowledge management and organizational learning", Journal of Knowledge Management, Vol. 4 No. 3, pp. 195--203.
• 21: Stacey, R. D. (2001), Complex Responsive Processes in Organizations -- Learning and Knowledge Creation, Routledge, London.
• 22: Gérard P. Cachon , Paul H. Zipkin , Philip Anderson, Complexity Theory and Organization Science, Organization Science, v.10 n.3, p.216-232, March 1999 [doi>10.1287/orsc.10.3.216]
• 23: Shawna Grosskopf , Kathy J. Hayes , Lori L. Taylor , William L. Weber , Arie Y. Lewin, Application of Complexity Theory to Organization Science, Organization Science, v.10 n.3, p.215-215, March 1999 [doi>10.1287/orsc.10.3.215]
• 24: Lewin, R. and Regine, B. (1999), "The soul at work -- unleashing the power of complexity science for business success", Orion Business, 1st ed., Orion Publishing Group Ltd, London.
• 25: McCarthy, I. P. (2003), "Technology management -- a complex adaptive systems approach", International Journal of Technology Management, Vol. 25 No. 8, pp. 728--45.
• 26: Nilsson, F and Darley, V. (2006), On complex adaptive systems and agent-based modelling for improving decision-making in manufacturing and logistics settings -- Experiences from a packaging company, International Journal of Operations & Production Management, 2006
• 27: Beinhocker, E. D. (1997), "Strategy at the edge of chaos", The McKinsey Quarterly, No. 1, pp. 24--39.
• 28: Murray Gell-Mann, The quark and the jaguar: adventures in the simple and the complex, W. H. Freeman & Co., New York, NY, 1995
• 29: Yaneer Bar-Yam, Dynamics of complex systems, Perseus Books, Cambridge, MA, 1997
• 30: Pascale, R. T. (1999), "Surfing the edge of chaos", Sloan Management Review, Vol. 40, pp. 83--95.
• 31: Stacey, R. D., Griffin, D. and Shaw, P. (2000), Complexity and Management -- Fad or Radical Challenge to Systems Thinking?, Routledge, London.
• 32: Joshua M. Epstein, Agent-based computational models and generative social science, Complexity, v.4 n.5, p.41-60, May/June 1999 [doi>10.1002/(SICI)1099-0526(199905/06)4:5<41::AID-CPLX9>3.0.CO;2-F]
• 33: Bonabeau, E. (2002), "Predicting the unpredictable", Harvard Business Review, Vol. 80 No. 3, pp. 109--16.
• 34: Prigogine, I. (1997), The End of Certainty -- Time, Chaos, and the New Laws of Nature, 1st ed., The Free Press, New York, NY.
• 35: Simon, H. A. (2002), "Near decomposability and the speed of evolution", Industrial and Corporate Change, Vol. 11 No. 3, pp. 587--99.
• 36: Nicholas R. Jennings , Katia Sycara , Michael Wooldridge, A Roadmap of Agent Research and Development, Autonomous Agents and Multi-Agent Systems, v.1 n.1, p.7-38, 1998 [doi>10.1023/A:1010090405266]
• 37: Robert Axelrod, Advancing the art of simulation in the social sciences, Complexity, v.3 n.2, p.16-22, Nov./Dec. 1997 [doi>10.1002/(SICI)1099-0526(199711/12)3:2<16::AID-CPLX4>3.0.CO;2-K]
• 38: Kauffman, S. (1995), At Home in the Universe: The Search for Laws of Self-Organization and Complexity, Oxford University Press, New York, NY.
• 39: M. North , C. Macal , P. Campbell, Oh behave! agent-based behavioral representations in problem solving environments, Future Generation Computer Systems, v.21 n.7, p.1192-1198, July 2005 [doi>10.1016/j.future.2004.04.006]
• 40: Mark d'Inverno , Michael Luck, Understanding agent systems, Springer-Verlag New York, Inc., New York, NY, 2001
• 41: Tripathi, A. K., Tiwari, M. K. and Chan, F. T. S. (2005), "Multi-agent-based approach to solve part selection and task allocation problem in flexible manufacturing systems", International Journal of Production Research, Vol. 43 No. 7, pp. 1313--35.
• 42: H. Van Dyke Parunak , Robert Savit , Rick L. Riolo, Agent-Based Modeling vs. Equation-Based Modeling: A Case Study and Users' Guide, Proceedings of the First International Workshop on Multi-Agent Systems and Agent-Based Simulation, p.10-25, July 04-06, 1998
• 43: Reaidy, J., Liu, Y., Diep, D. and Massotte, P. (2003), "Intelligent agents for production systems", in d'Amours, S. and Guinet, A. (Eds), Intelligent Agent-Based Operations Management, Kogan Page Ltd, London, pp. 147--64.
• 44: Swaminathan, J. M., Smith, S. F. and Sadeh, N. M. (1998), "Modeling supply chain dynamics: a multiagent approach", Decision Sciences, Vol. 29 No. 3, pp. 607--32
• 45: Annapurna Valluri , David C. Croson, Agent learning in supplier selection models, Decision Support Systems, v.39 n.2, p.219-240, April 2005 [doi>10.1016/j.dss.2003.10.008]
• 46: Garcia, R. (2005), "Uses of agent-based modeling in innovation/new product development research", The Journal of Product Innovation Management, Vol. 22 No. 1, pp. 380--98.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.3 Group and Organization Interfaces

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.3 Group and Organization Interfaces

General Terms:
Algorithms, Human Factors, Theory

Keywords:
agent based modeling, collaboration, knowledge management, multi-agent systems, wikipedia