Wayfinding in Social Networks

With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon – the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends – and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.

[1]  Jon M. Kleinberg,et al.  Spatial variation in search engine queries , 2008, WWW.

[2]  D. Watts,et al.  An Experimental Study of Search in Global Social Networks , 2003, Science.

[3]  G. Simmel,et al.  Conflict and the Web of Group Affiliations , 1955 .

[4]  Kevin Lynch,et al.  The Image of the City , 1960 .

[5]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[6]  Pierre Fraigniaud,et al.  A Doubling Dimension Threshold Theta(loglogn) for Augmented Graph Navigability , 2006, ESA.

[7]  Beom Jun Kim,et al.  Path finding strategies in scale-free networks. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  Andrew Tomkins,et al.  Navigating Low-Dimensional and Hierarchical Population Networks , 2006, ESA.

[9]  Moni Naor,et al.  Know thy neighbor's neighbor: the power of lookahead in randomized P2P networks , 2004, STOC '04.

[10]  Nicolas Schabanel,et al.  Close to optimal decentralized routing in long-range contact networks , 2005, Theor. Comput. Sci..

[11]  Jon M. Kleinberg,et al.  The small-world phenomenon: an algorithmic perspective , 2000, STOC '00.

[12]  Aleksandrs Slivkins Distance estimation and object location via rings of neighbors , 2005, PODC '05.

[13]  Pierre Fraigniaud,et al.  Eclecticism shrinks even small worlds , 2004, PODC.

[14]  A. Zander,et al.  Group dynamics, research and theory , 1955 .

[15]  Filippo Menczer,et al.  Growing and navigating the small world Web by local content , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Michael Mitzenmacher,et al.  A Brief History of Generative Models for Power Law and Lognormal Distributions , 2004, Internet Math..

[17]  Charles U. Martel,et al.  Augmented Graph Models for Small-World Analysis with Geographic Factors , 2008, ANALCO.

[18]  F. Heider,et al.  Principles of topological psychology , 1936 .

[19]  R. Langer,et al.  Where a pill won't reach. , 2003, Scientific American.

[20]  J. Kleinfeld COULD IT BE A BIG WORLD AFTER ALL? THE "SIX DEGREES OF SEPARATION" MYTH , 2002 .

[21]  César A. Hidalgo,et al.  Scale-free networks , 2008, Scholarpedia.

[22]  Jon M. Kleinberg,et al.  Navigation in a small world , 2000, Nature.

[23]  Cristopher Moore,et al.  How Do Networks Become Navigable , 2003 .

[24]  Béla Bollobás,et al.  The degree sequence of a scale‐free random graph process , 2001, Random Struct. Algorithms.

[25]  Charles U. Martel,et al.  Analyzing Kleinberg's (and other) small-world Models , 2004, PODC '04.

[26]  Ian Clarke,et al.  The evolution of navigable small-world networks , 2006, ArXiv.

[27]  Luis Russo,et al.  Who shall survive?: Foundations of sociometry group psychotherapy and sociodrama , 2010 .

[28]  Eli Upfal,et al.  Stochastic models for the Web graph , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[29]  Nicolas Schabanel,et al.  Almost Optimal Decentralized Routing in Long-Range Contact Networks , 2004, ICALP.

[30]  Sharon L. Milgram,et al.  The Small World Problem , 1967 .

[31]  Pierre Fraigniaud,et al.  Networks Become Navigable as Nodes Move and Forget , 2008, ICALP.

[32]  Lada A. Adamic,et al.  Search in Power-Law Networks , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[33]  Lada A. Adamic,et al.  How to search a social network , 2005, Soc. Networks.

[34]  Jacob L. Moreno,et al.  Who shall survive? : foundations of sociometry, group psychotherapy, and sociodrama , 1953 .

[35]  Pierre Fraigniaud,et al.  Greedy Routing in Tree-Decomposed Graphs , 2005, ESA.

[36]  Frank Harary,et al.  Graph Theory As A Mathematical Model In Social Science , 1953 .

[37]  George Kachergis,et al.  Depth of Field and Cautious-Greedy Routing in Social Networks , 2007, ISAAC.

[38]  M E J Newman,et al.  Identity and Search in Social Networks , 2002, Science.

[39]  J. Kleinfeld,et al.  The small world problem , 2002 .

[40]  M. Mitzenmacher A brief history of lognormal and power law distributions , 2001 .

[41]  Charles U. Martel,et al.  Analyzing and characterizing small-world graphs , 2005, SODA '05.

[42]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[43]  Philippe Duchon,et al.  Towards small world emergence , 2006, SPAA '06.

[44]  Lali Barrière,et al.  Efficient Routing in Networks with Long Range Contacts , 2001, DISC.

[45]  David D. Jensen,et al.  Decentralized Search in Networks Using Homophily and Degree Disparity , 2005, IJCAI.

[46]  Pierre Fraigniaud,et al.  Small Worlds as Navigable Augmented Networks: Model, Analysis, and Validation , 2007, ESA.

[47]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[48]  P. Killworth,et al.  The reversal small-world experiment , 1978 .

[49]  Jasmine Novak,et al.  Geographic routing in social networks , 2005, Proc. Natl. Acad. Sci. USA.

[50]  Jon M. Kleinberg,et al.  Small-World Phenomena and the Dynamics of Information , 2001, NIPS.

[51]  Lada A. Adamic,et al.  Local Search in Unstructured Networks , 2002, ArXiv.