Fractal multi-level organisation of human groups in a virtual world

Humans are fundamentally social. They form societies which consist of hierarchically layered nested groups of various quality, size, and structure. The anthropologic literature has classified these groups as support cliques, sympathy groups, bands, cognitive groups, tribes, linguistic groups, and so on. Anthropologic data show that, on average, each group consists of approximately three subgroups. However, a general understanding of the structural dependence of groups at different layers is largely missing. We extend these early findings to a very large high-precision large-scale internet-based social network data. We analyse the organisational structure of a complete, multi-relational, large social multiplex network of a human society consisting of about 400,000 odd players of an open-ended massive multiplayer online game for which we know all about their various group memberships at different layers. Remarkably, the online players' society exhibits the same type of structured hierarchical layers as found in hunter-gatherer societies. Our findings suggest that the hierarchical organisation of human society is deeply nested in human psychology.

[1]  A. Arenas,et al.  Community analysis in social networks , 2004 .

[2]  Serguei Saavedra,et al.  A simple model of bipartite cooperation for ecological and organizational networks , 2009, Nature.

[3]  Keith F. Otterbein,et al.  Reconsidering Violence in Simple Human Societies: Homicide among the Gebusi of New Guinea [and Comments and Reply] , 1987, Current Anthropology.

[4]  Ayşe Erzan,et al.  Finite q-differences and the discrete renormalization group , 1997 .

[5]  Didier Sornette,et al.  Evidence of intermittent cascades from discrete hierarchical dissipation in turbulence , 2001, cond-mat/0110436.

[6]  Robin I. M. Dunbar.  Coevolution of neocortical size, group size and language in humans , 1993, Behavioral and Brain Sciences.

[7]  Vito Latora,et al.  Understanding mobility in a social petri dish , 2011, Scientific Reports.

[8]  Stefan Thurner,et al.  Triadic closure dynamics drives scaling laws in social multiplex networks , 2013, 1301.0259.

[9]  Robin I. M. Dunbar,et al.  Social networks, support cliques, and kinship , 1995, Human nature.

[10]  D. Sornette.  Discrete scale invariance and complex dimensions , 1997, cond-mat/9707012.

[11]  Didier Sornette,et al.  Generalized q analysis of log-periodicity: applications to critical ruptures. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Robin I. M. Dunbar,et al.  Social network size in humans , 2003, Human nature.

[13]  Serguei Saavedra,et al.  Strong contributors to network persistence are the most vulnerable to extinction , 2011, Nature.

[14]  Acknowledgments , 2006, Molecular and Cellular Endocrinology.

[15]  J. Steward,et al.  Theory of Culture Change: The Methodology of Multilinear Evolution , 1990 .

[16]  Bruce T. Milne,et al.  The complex structure of hunter–gatherer social networks , 2007, Proceedings of the Royal Society B: Biological Sciences.

[17]  Michael Szell,et al.  Measuring social dynamics in a massive multiplayer online game , 2009, Soc. Networks.

[18]  William H. Press,et al.  Numerical recipes , 1990 .

[19]  Michael Szell,et al.  How women organize social networks different from men , 2012, Scientific Reports.

[20]  W. Bainbridge.  The Scientific Research Potential of Virtual Worlds , 2007, Science.

[21]  Stephen Shennan,et al.  Constructing frames of reference: An analytical method for archaeological theory building using ethnographic and environmental data sets , 2004 .

[22]  Robin I. M. Dunbar.  Social cognition on the Internet: testing constraints on social network size , 2012, Philosophical Transactions of the Royal Society B: Biological Sciences.

[23]  Michael Szell,et al.  Emergence of Good Conduct, Scaling and Zipf Laws in Human Behavioral Sequences in an Online World , 2012, PloS one.

[24]  Didier Sornette,et al.  Statistical Significance of Periodicity and Log-Periodicity with Heavy-Tailed Correlated Noise , 2002 .

[25]  Michalis Vazirgiannis,et al.  On Clustering Validation Techniques , 2001, Journal of Intelligent Information Systems.

[26]  Jean-Pierre Eckmann,et al.  Q-ANALYSIS OF FRACTAL SETS , 1997 .

[27]  Robin I. M. Dunbar.  CO-EVOLUTION OF NEOCORTEX SIZE , GROUP SIZE AND LANGUAGE IN HUMANS , 2008 .

[28]  Michael Szell,et al.  Multirelational organization of large-scale social networks in an online world , 2010, Proceedings of the National Academy of Sciences.

[29]  Didier Sornette,et al.  Discrete hierarchical organization of social group sizes , 2004, Proceedings of the Royal Society B: Biological Sciences.

[30]  Didier Sornette,et al.  NONPARAMETRIC ANALYSES OF LOG-PERIODIC PRECURSORS TO FINANCIAL CRASHES , 2003 .

[31]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[32]  C. Mallows,et al.  A Method for Comparing Two Hierarchical Clusterings , 1983 .

[33]  Werner Ulrich,et al.  A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement , 2008 .

[34]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[35]  Stefan Thurner,et al.  Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World , 2014, PloS one.

[36]  Katharina Burger,et al.  The Kung San Men Women And Work In A Foraging Society , 2016 .

[37]  R. Alexander Bentley,et al.  Network scaling reveals consistent fractal pattern in hierarchical mammalian societies , 2008, Biology Letters.

[38]  Albert-László Barabási,et al.  Hierarchical organization in complex networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.