Small Worlds and Cultural Polarization

Building on Granovetter's theory of the “strength of weak ties,” research on “small-world” networks suggests that bridges between clusters in a social network (long-range ties) promote cultural diffusion, homogeneity, and integration. We show that this macro-level implication of network structure depends on hidden micro-level assumptions. Using a computational model similar to earlier studies, we find that ties between clusters facilitate cultural convergence under the micro-level assumptions of assimilation and attraction to similar others. However, these assumptions also have negative counterparts—differentiation and xenophobia. We found that when these negative possibilities are no longer assumed away, the effect of long-range ties reverses: Even very small amounts of contact between highly clustered communities sharply increased polarization at the population level. [An appendix to this article is featured as an online supplement at the publisher's website.]

[1]  Yasufumi Shibanai,et al.  Effects of Global Information Feedback on Diversity , 2001 .

[2]  D. Watts.  Networks, Dynamics, and the Small‐World Phenomenon1 , 1999, American Journal of Sociology.

[3]  S. Levin,et al.  The dynamics of political polarization , 2021, Proceedings of the National Academy of Sciences.

[4]  Rainer Hegselmann,et al.  Opinion dynamics and bounded confidence: models, analysis and simulation , 2002, J. Artif. Soc. Soc. Simul..

[5]  Noah Mark,et al.  Beyond individual differences : Social differentiation from first principles , 1998 .

[6]  M. Macy,et al.  Agent based modelling: social order from the bottom up , 2009 .

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

[8]  P. Lazarsfeld,et al.  Friendship as Social process: a substantive and methodological analysis , 1964 .

[9]  R. Ralph,et al.  Social Pressures in Informal Groups. , 1951 .

[10]  J. French.  A formal theory of social power. , 1956, Psychology Review.

[11]  N. Denton,et al.  Hypersegregation in U.S. Metropolitan Areas: Black and Hispanic Segregation Along Five Dimensions , 1989, Demography.

[12]  Andreas Flache,et al.  How to get the timing right. A computational model of the effects of the timing of contacts on team cohesion in demographically diverse teams , 2008, Comput. Math. Organ. Theory.

[13]  Noah E. Friedkin,et al.  Social influence and opinions , 1990 .

[14]  Andreas Flache,et al.  Why do faultlines matter? A computational model of how strong demographic faultlines undermine team cohesion , 2008, Simul. Model. Pract. Theory.

[15]  Michael W. Macy,et al.  Structural Learning: Attraction and Conformity in Task-Oriented Groups , 1999, Comput. Math. Organ. Theory.

[16]  D. Murphey,et al.  The World Is Flat: A Brief History of the Twenty-First Century , 2006 .

[17]  Morroe Berger,et al.  Freedom and control in modern society , 1954 .

[18]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Vincent J. Roscigno,et al.  White Supremacists, Oppositional Culture and the World Wide Web , 2005 .

[20]  V. Eguíluz,et al.  Global culture: a noise-induced transition in finite systems. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  James A. Kitts,et al.  Social influence and the emergence of norms amid ties of amity and enmity , 2006, Simul. Model. Pract. Theory.

[22]  M. Macy,et al.  Complex Contagions and the Weakness of Long Ties1 , 2007, American Journal of Sociology.

[23]  Ray Bert,et al.  Book Review: \IThe World Is Flat: A Brief History of the Twenty-First Century\N by Thomas L. Friedman. New York: Farrar, Straus and Giroux, 2005 , 2006 .

[24]  E. Glaeser,et al.  Myths and Realities of American Political Geography , 2005 .

[25]  Mark S. Granovetter.  The Strength of Weak Ties , 1973, American Journal of Sociology.

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

[27]  Noah E. Friedkin,et al.  Norm formation in social influence networks , 2001, Soc. Networks.

[28]  Wander Jager,et al.  Uniformity, Bipolarization and Pluriformity Captured as Generic Stylized Behavior with an Agent-Based Simulation Model of Attitude Change , 2005, Comput. Math. Organ. Theory.

[29]  Kathleen M. Carley,et al.  Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers , 2004 .

[30]  C. Earley,et al.  Creating hybrid team cultures: An empirical test of transnational team functioning. , 2000 .

[31]  V. Eguíluz,et al.  Nonequilibrium transitions in complex networks: a model of social interaction. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[32]  B A Huberman,et al.  Evolutionary games and computer simulations. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[33]  Jeroen Weesie,et al.  Consent or Conflict: Coevolution of Coordination and Networks , 2008 .

[34]  Bradley L. Kirkman,et al.  Five challenges to virtual team success: Lessons from Sabre, Inc. , 2002 .

[35]  M. Macy.  Polarization in Dynamic Networks : A Hopfield Model of Emergent Structure , 2003 .

[36]  Noah Mark,et al.  Culture and Competition: Homophily and distancing Explanations for Cultural Niches , 2003, American Sociological Review.

[37]  R. Axelrod.  The Dissemination of Culture , 1997 .