Abstract
Guild sizes for five massive multiplayer online game guilds, and their aggregate data set, were analyzed and tested for fit against four candidate distributional models: power law, linear, exponential, and log-normal. Results provide very strong support of a power law distribution, especially in the aggregated data set, for which all other distributions were rejected. This indicates that a non-equilibrium, scale-free process underlies the dynamics of guild formation. One can conclude that social processes that generate similar distributions in “real world” organizations are extendable to social life in virtual worlds.
I would like to thank Claudio Cioffi-Revilla for guidance provided while instructing the graduate seminar “Computational Analysis of Social Complexity” (Spring 2014, GMU), and to classmates from the same who brought my attention to the methods of CSN 2009 and VC 2014 (referenced in the paper) for testing power law distributions and working with binned data.
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References
Axtell, R.L.: Zipf distribution of U.S. firm sizes. Science 293, 1818–1820 (2001)
Barabasi, A., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)
Clauset, A., Shalizi, C.R., Newman, M.E.: Power-law distributions in empirical data. SIAM Review 51, 661–703 (2009)
Liljeros, F.: The effect of social clustering on the size of vol- untary organizations. In: Cioffi-Revilla, C. (Ed.), Power Laws and Non-equilibrium Distributions of Complexity in the Social Sciences (pp. 66–75). Fairfax, VA: open source (2008)
Liljeros, F., Amaral, L.A., Stanley, H.E.: Universal mecha- nisms in the growth of voluntary organizations (2003). Retrieved from arxiv.org/abs/nlin/0310001
MMORPG Guild List. (2014, May). Retrieved from www.mmorpg.com/guilds.cfm/
Virkar, Y., Clauset, A.: Power-law distributions in binned empirical data. Annals of Applied Statistics 8(1), 89–119 (2014)
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Kane, V. (2015). Social Complexity in the Virtual World . In: Agarwal, N., Xu, K., Osgood, N. (eds) Social Computing, Behavioral-Cultural Modeling, and Prediction. SBP 2015. Lecture Notes in Computer Science(), vol 9021. Springer, Cham. https://doi.org/10.1007/978-3-319-16268-3_9
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DOI: https://doi.org/10.1007/978-3-319-16268-3_9
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