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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 social influence, homophily, and xenophobia can lead to cultural polarization, 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. Incomplete polarization is also possible, with agents aligned on a small number of cross-cutting dimensions.





Michael W. Macy

Goldwin Smith Professor of Arts and Sciences
Department of Sociology
Department of Information Science
Director, Social Dynamics Laboratory
Cornell University
Ithaca, NY 14853
Voice: (607) 255-4555
Fax: (607) 202-4913
Email: mwm14@cornell.edu




Click here for Networks and Social Dynamics at Cornell

Click here for Nature feature story by Jim Giles on computational social science at Cornell

Click here for iTunes U video on "Getting Connected" at Cornell's Institute for the Social Sciences

Click here for Oct 2011 "Naked Scientist" interview on BBC

Click here for Seti Institute's "Big Picture Science" interview on Public Radio

Click here for my CV


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 (e.g., pressuring one's neighbors to support various "naked emperors"). 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 "big data" from online networks to look for elementary principles of social interaction that may yield clues about possible answers to these and related puzzles about human behavior. Recent studies with Damon Centola, Vladimir Barash, and Chris Cameron 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. A related analysis of a nearly complete set of telephone logs from the UK (with Nathan Eagle and Rob Claxton) indicates that small worlds also seem to be associated with economic development. In another study tracking "digital footprints," Scott Golder and I analyzed the affective content of global Twitter messages to reveal remarkable similarity in diurnal and seasonal mood variations across diverse cultures.

Current projects (collaborators listed aphabetically):

  • Why liberals drink lattes (with Daniel DellaPosta and Yongren Shi)
  • Using Twitter to study mobilization in Arab Spring (with Jon Kleinberg, Noona Oh, Michael Siemon, Silvana Toska, and Shaomei Wu, supported by NSF)
  • How random perturbations can make social dynamics more predictable (with Milena Tsvetkova)
  • Using social media to study the cultural and economic correlates of network structure (with Patrick Park, Bogdan State, Ingmar Weber, and Yelena Mejova, supported by NSF)
  • Whether social media attenuate or reinforce social class boundaries (with David Grusky and Bogdan State)
  • Using an MMOG to study intergroup conflict and cooperation (with Dustin Chertoff and Milena Tsvetkova, supported by NSF)
  • The puzzle of "three degrees of influence" (with Chris Cameron)
  • Using Amazon book purchases to measure political and cultural polarization (with Fedor Dokshin and Yongren Shi)
  • Using online experiments to study the willingness to "pay it forward" (with Milena Tsvetkova, supported by NSF)

    I have listed below some of my papers that you are welcome to download. Some papers require access to JSTOR or other archives; if your university does not provide access, please email me and I will send you a digital copy.


    The Social Contagion of Generosity
    Milena Tsvetkova and Michael Macy
    PLOS One Feb. 13, 2014: 9(2): e87275


    Statistical Mechanics and Social Sciences
    Santo Fortunato, Michael Macy, Sidney Redner
    Journal of Statistical Physics 2013, 151:1-8


    Critical Phenomena in Complex Contagions
    Vladimir Barash, Chris Cameron, and Michael Macy
    Social Networks 2012, 34:451-61


    Diurnaland Seasonal Mood Vary with Work, Sleep and Daylength Across Diverse Cultures
    Scott Golder and Michael Macy
    Science 2011, 333:1878-81


    Small Worlds and Cultural Polarization
    Andreas Flache and Michael Macy
    Journal of Mathematical Sociology 2011, 34: 146-76


    Local Convergence and Global Diversity: From Interpersonal to Social
    Influence

    Andreas Flache and Michael Macy
    Journal of Conflict Resolution 2011, 55: 970-95


    Network Diversity and Economic Development
    Nathan Eagle, Rob Claxton, and Michael Macy
    Science 2010, 328: 1029-1031


    Computational Social Science
    David Lazer et al.
    Science 2009, 323: 712-723


    The False Enforcement of Unpopular Norms
    Rob Willer, Ko Kuwabara, and Michael Macy
    American Journal of Sociology 2009, 115:451-490


    Neighborhood Chance and Neighborhood Change
    Arnout Van de Rijt, David Siegel, and Michael Macy
    American Journal of Sociology 2009, 114:1166-80


    Complex Contagions and the Weakness of Long Ties
    Damon Centola and Michael 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 Macy
    Physica A 2007, 374: 449-456


    Power and Dependence in Intimate Exchange
    Arnout van de Rijt, and Michael Macy
    Social Forces 2006, 84:1455-70


    Ethnic Preferences and Residential Segregation: Theoretical Explorations Beyond Detroit
    Michael Macy and Arnout van de Rijt
    Journal of Mathematical Sociology 2006, 30: 275-88


    The Emperor's Dilemma: A Computational Model of Self-Enforcing Norms
    Damon Centola, Robb Willer, and Michael Macy
    American Journal of Sociology 2005, 110:1009-40


    Social Life in Silico: The Science of Artificial Societies
    Damon Centola and Michael Macy
    Handbook of Group Research and Practice 2005, pp. 273-2812


    Power, Identity, and Collective Action in Social Exchange
    Brent Simpson and Michael Macy
    Social Forces, June, 2004.


    Polarization in Dynamic Networks: A Hopfield Model of Emergent Structure
    Michael Macy, James Kitts, Andreas Flache, and Steve Benard
    Dynamic Social Network Modeling and Analysis, National Academy Press, 2003


    Learning Dynamics in Social Dilemmas
    Michael Macy and Andreas Flache
    Proceedings of the National Academy of Sciences, May 14, 2002.


    Stochastic Collusion and the Power Law of Learning
    Andreas Flache and Michael Macy
    Journal of Conflict Resolution, October, 2002


    From Factors to Actors: Computational Sociology and Agent-Based Modeling
    Michael Macy and Robert Willer
    Annual Review of Sociology, Vol. 28, 2002


    Trust and Market Formation in the U.S. and Japan
    Michael Macy and Yoshimichi Sato
    Proceedings of the National Academy of Sciences, April, 2002
    Source code for the computational model


    Social Simulation
    Michael W. Macy
    In N. Smelser and P. Baltes, eds., International Encyclopedia of the Social and Behavioral Sciences, Elsevier, 2002


    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.


    'In Search ofExcellence': Fads, Success Stories, and Adaptive Emulation*
    David Strang and Michael 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


    Collective Action and Power Inequality: Coalitions in Exchange Networks*
    Brent Simpson and Michael Macy
    Social Psychology Quarterly, March, 2001.
    *Preprint not identical to published version.


    Structural Learning: Attraction and Conformity in Task-Oriented Groups
    James Kitts, Michael Macy, and Andreas Flache
    Computational and Mathematical Organization Theory, 1999, vol. 5(2):129-45.


    Unlocking the Doors to Prisoners Dilemma: Dependence, Selectivity, and Cooperation
    R. Thomas Boone and Michael Macy
    Social Psychology Quarterly 1999, 62: 32-52.


    The Evolution of Trust and Cooperation between Strangers: A Computational Model*
    Michael 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 Order and Emergent Rationality
    Michael Macy
    In A. Sica, ed. Whatis Social Theory: The Philosophical Debates, 1998, Blackwell.


    Dependence and Cooperation in the Game of Trump
    R. Thomas Boone and Michael Macy
    Advances in Group Processes, vol. 15, 1998


    Social Order in an Artificial World
    Michael W. Macy
    Journal of Artificial Societies and Social Simulation, January, 1998.


    The Weakness of Strong Ties II: Collective Action Failure in a Self-Organizing Social Network
    Michael Macy , James Kitts, and Andreas Flache
    Presented at American Sociological Association, Toronto, August 11, 1997.


    Identity, Interest, and Emergent Rationality: An Evolutionary Synthesis
    Michael Macy
    Rationality and Society, vol. 9, 1997.


    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.