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An Attractor Neural Network Model of Cultural Polarization
Why are political views on taxes and spending highly correlated with views on same-sex marriage, gun control, reproductive rights, and consumer preferences like Subaru vs. Dodge Ram, lattes vs. black coffee, Sam Adams vs. Budweiser, and so on? An agent based model of selective influence suggests a simple explanation: people are attracted to those with similar cultural preferences, repelled by those with salient differences, and are positively and negatively influenced by those to whom they are attracted/repelled. The model consists of 100 fully connected agents with initially random traits on 10 cultural features. The axes displayed above are the two principle eigenvectors from the 10-dimensional sociomatrix. The size of the circle indicates the number of agents with that cultural profile. Multiple runs show how the dynamics of homophily and xenophobia inevitably lead to cultural polarization along one and occasionally two dimensions, such that agents at each pole have identical traits on all ten cultural features and are maximally dissimilar to the agents at the opposite pole. Thus, from a random start, all 45 pairwise cultural dimensions come to be highly correlated, but the signs of the correlations are in all cases entirely arbitrary.
Michael W. Macy
Goldwin Smith Professor of Arts and Sciences
Department of Sociology
Department of Information Science
Director, Social Dynamics Laboratory
372 Uris Hall
Cornell University
Ithaca, NY 14853
Voice: (607) 255-4555
Fax: (607) 202-4913
Email: mwm14@cornell.edu
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Areas of interest: collective action, noms, intergroup conflict, diffusion on complex networks, social influence.
Methods:
Agent-based
modeling, laboratory experiments, analysis of on-line networks.
Why does our world not degenerate into the world of Mad Max -- and why does it sometimes seem as if it may? Social order among interdependent agents can be imposed "from above" by a global policing mechanism or it can emerge "from below" through local interactions among adaptive agents with no centralized coordination. Suppose no member of the population has the ability to identify or impose a global solution. How then is social order possible? My research explores how norms, opinions, emotions, and collective action emerge and spread through local interaction. The motivating problem is one that defines the human condition: the overwhelming need for norms that constrain aggressive and mutually destructive behavior is no guarantee that such rules will emerge or be obeyed by anyone except a few "suckers." On the contrary, norms can even make matters worse, by obligating people to engage in behaviors that are individually and collectively harmful. It is not hard to explain why people comply with socially undesirable norms in the face of social pressure, but why would a skeptical population enforce these norms in the first place? My research team uses computational models, laboratory experiments with human subjects, and data from online networks to look for elementary principles of social interaction that may yield clues about possible answers. Recent studies have focused on the spread of "complex contagions" that depend on social reinforcement from several network neighbors. We found that small world networks that are optimal for the spread of information and disease can inhibit the diffusion of risky or costly collective behaviors characterized by high thresholds of adoption.
Current projects (collaborators listed aphabetically):
Using Twitter messages to measure diurnal and seasonal mood variations across diverse dultures (with Scott Golder)
Using Twitter content from the Middle East to track the spread of Arab Spring (with Jon Kleinberg, Noona Oh, Michael Siemon, Silvana Toska, and Shaomei Wu)
The effects of noise on social dynamics (with Milena Tsvetkova)
Critical phenomena in complex contagions (with Vladimir Barash and Chris Cameron)
The cultural and economic correlates of network structure (with Nathan Eagle, Rob Claxton, and Patrick Park)
Cultural differentiation and assimilation in dynamic networks (with Andreas Flache)
I have listed below some of my papers that you are welcome to download. Some papers require access to JSTOR or INGENTA; if your university does not provide access, please email me and I will send you a digital copy.
Diurnal and Seasonal Mood Vary with Work, Sleep and Daylength Across Diverse Cultures
Scott Golder and Michael W. Macy
Science 2011, 333:1878-81.
Small Worlds and Cultural Polarization
Andreas Flache and Michael W. Macy et al.
Journal of Mathematical Sociology 2011, 34: 146-76.
Network Diversity and Economic Development
Nathan Eagle, Rob Claxton, and Michael W. Macy
Science 2010, 328: 1029-1031.
Computational Social Science
David Lazer et al.
Science 2009, 323: 721 – 723.
The False Enforcement of Unpopular Norms
Rob Willer, Ko Kuwabara, and Michael W. Macy
American Journal of Sociology 2009, 115:451–490.
Neighborhood Chance and Neighborhood Change
Arnout Van de Rijt, David Siegel, and Michael W. Macy
American Journal of Sociology 2009, 114:1166-80.
Complex
Contagions and
the Weakness of Long Ties
Damon Centola and Michael W. Macy
American Journal of Sociology 2007, 113:702-34.
Culture,
Identity, and
Structure in Social Exchange: A Web-based Trust Experiment in the U.S.
and
Japan
Kuwabara,
K., R. Willer,
M. Macy, R. Mashima, S. Terai,
and T. Yamagishi
Social Psychology Quarterly, 2007, 70:461-79.
Collective
Action and the Empirical Content of Stochastic Learning Models
M. Macy and A. Flache
American Journal of Sociology, 2007,
112: 1546-54.
Cascade
Dynamics of
Complex Propagation
Damon Centola, Victor M. Eguiluz,
and Michael W. Macy
Physica A 2007, 374: 449-456
Power and Dependence in Intimate Exchange
Arnout van de Rijt, and Michael W. Macy
Social Forces 2006, 84:1455-70.
The Emperor’s Dilemma: A Computational Model of Self-Enforcing Norms
Damon Centola,
Robb Willer, and Michael W. Macy
American Journal of Sociology 2005, 110:1009-40.
Social Life in Silico: The Science of Artificial Societies
Damon Centola and Michael W. Macy
Handbook of Group Research and Practice 2005, pp. 273-281.
Polarization in Dynamic Networks: A Hopfield Model of Emergent Structure
Michael W. Macy, James Kitts,
Andreas Flache, and Steve Benard
Dynamic Social Network Modeling and Analysis,
Learning Dynamics in Social Dilemmas
Michael W. Macy and Andreas Flache
Proceedings of the
Stochastic
Collusion and the Power Law of Learning
Andreas Flache and Michael W. Macy
Journal of Conflict Resolution, October, 2002.
From
Factors to Actors: Computational Sociology and Agent-Based Modeling
Michael W. Macy and Robert Willer
Annual Review of Sociology, Vol. 28, 2002
Trust and
Market
Formation in the U.S. and Japn
Michael W. Macy and Yoshimichi Sato
Proceedings of the
Source code for the computational model
'In Search ofExcellence': Fads, Success Stories, and Adaptive Emulation*
David Strang
and Michael W. Macy
Best Paper Proceedings of the 1999 Academy of Management Conference, Chicago,IL
American Journal of Sociology, July, 2001.
*HTML Preprint not identical to published version.
The Evolution of Trust and Cooperation between
Strangers:
A Computational Model*
Michael W. Macy and John Skvoretz
American Sociological Review, October, 1998.
Presented at the Sante Fe Institute,
August 6, 1996
*HTML Preprint not identical to published version.
Social
Simulation
Michael W. Macy
In N. Smelser and P. Baltes,
eds., International Encyclopedia of the Social
and Behavioral Sciences, Elsevier, 2002
Power,
Identity, and
Collective Action in Social Exchange
Brent Simpson and Michael W. Macy
Social Forces, June, 2004.
Collective
Action and Power Inequality: Coalitions in Exchange Networks*
Brent Simpson and Michael W. Macy
Social Psychology Quarterly, March, 2001.
*Preprint not identical to published version.
Dependence
and
Cooperation in Fuzzy Dilemmas:
The Effects of Environmental and Endowment Uncertainty
R. Thomas Boone and Michael W. Macy
In R. Suleiman, D. Budescu, & D. Messick, eds., ContemporaryPsychological
Research on Social Dilemmas
Cambridge University Press, 2002.
The Weakness of Strong Ties II:
Collective Action Failure in a Self-Organizing Social Network
Michael W. Macy , James Kitts, and
Andreas Flache
Presented at American Sociological Association,
Structural
Learning: Attraction and Conformity in Task-Oriented Groups
James Kitts, Michael W. Macy, and Andreas Flache
Computational and Mathematical Organization Theory, 1999,
vol. 5(2):129-45.
Identity,
Interest, and Emergent Rationality: An Evolutionary Synthesis
Michael W. Macy
Rationality and Society, vol. 9, 1997.
Dependence
and
Cooperation in the Game of Trump
R. Thomas Boone and Michael W. Macy
Presented at International Conference on Group Process, Krakov,Poland,
August, 1996
Advances in Group Processes, vol. 15, 1998.
Dependence,
Selectivity, and Cooperation
R. Thomas Boone and Michael W. Macy
Presented at the annual meeting of the American Sociological Association,
Social Psychology Quarterly, March, 1999.
Social
Order and Emergent Rationality
Michael W. Macy
Presented at ASA Theory Section Miniconference,1996.
In A. Sica, ed. Whatis
Social Theory: The Philosophical Debates, 1998, Blackwell.
Social
Order in an Artificial World
Michael W. Macy
Journal of Artificial Societies and Social Simulation,
January, 1998.
The Weakness of Strong Ties:
Collective Action Failure in a Highly Cohesive Group
Andreas Flache and Michael W. Macy
Journal of Mathematical Sociology, June, 1996
Natural
Selection
and Social Learning in Prisoner's Dilemma:
Co-adaptationwith Genetic Algorithms and Artificial
Neural
Networks
Michael W. Macy
Sociological Methods and Research, Vol
25,
August, 1996, pp. 103-137
Beyond
Rationality in Models of Choice
Michael W. Macy and Andreas Flache
Annual Review of Sociology, Vol. 21, 1995
PAVLOV
and the Evolution of Cooperation: An Experimental Test
Michael W. Macy
Social Psychology Quarterly, June, 1995
Artificial
Social Intelligence
William Bainbridge, Edward Brent, David Heise,
Michael Macy, Barry Markovsky, & John Skvoretz
Annual Review of Sociology, Vol. 21, 1995
Once Upon a
Time
There Was a Suboptimal Equilibrium
Michael W. Macy
The Agora, June, 1996
Cowardly
Lions:
Genetic Programming or Social Learning?
Michael W. Macy
The Agora, December,
1995
Social
Class
Michael W. Macy
The Encyclopedia of Language and Linguistics
Backward-Looking
Social Control
Michael W. Macy
American Sociological Review, 1993, Vol. 58:819-36.
Chains
of Cooperation: Threshold Effects in Collective Action
Michael W. Macy
American Sociological Review, 1991, Vol. 56:730-47.
Learning to Cooperate: Stochastic and Tacit Collusion in
Social
Exchange
Michael W. Macy
American Journal of Sociology, 1991, Vol. 97:808-43.
Learning
Theory and the Logic of Critical Mass
Michael W. Macy
American Sociological Review, 1990, Vol. 55:809-26.
Value Theory and the Golden Eggs: Appropriating the Magic of Accumulation
Michael W. Macy
Sociological Theory, 1988, Vol. 6: 131-52.