Social Influences in the Voter Model: the Role of Conformity

We study the effects of social influences in opinion dynamics. In particular, we define a simple model, based on the majority rule voting, in order to consider the role of conformity. Conformity is a central issue in social psychology as it represents one of people’s behaviors that emerges as a result of their interactions. The proposed model represents agents, arranged in a network and provided with an individual behavior, that change opinion in function of those of their neighbors. In particular, agents can behave as conformists or as nonconformists. In the former case, agents change opinion in accordance with the majority of their social circle (i.e., their neighbors); in the latter case, they do the opposite, i.e., they take the minority opinion. Moreover, we investigate the nonconformity both on a global and on a local perspective, i.e., in relation to the whole population and to the social circle of each nonconformist agent, respectively. We perform a computational study of the proposed model, with the aim to observe if and how the conformity affects the related outcomes. Moreover, we want to investigate whether it is possible to achieve some kind of equilibrium, or of order, during the evolution of the system. Results highlight that the amount of nonconformist agents in the population plays a central role in these dynamics. In particular, conformist agents play the role of stabilizers in fully-connected networks, whereas the opposite happens in complex networks. Furthermore, by analyzing complex topologies of the agent network, we found that in the presence of radical nonconformist agents the topology of the system has a prominent role; otherwise it does not matter since we observed that a conformist behavior is almost always more convenient. Finally, we analyze the results of the model by considering that agents can change also their behavior over time, i.e., conformists can become nonconformists and vice versa.

[1]  André C. R. Martins,et al.  The building up of individual inflexibility in opinion dynamics , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Giuliano Armano,et al.  Perception of similarity: a model for social network dynamics , 2013 .

[3]  S Redner,et al.  Majority versus minority dynamics: phase transition in an interacting two-state spin system. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  S. Redner,et al.  Dynamics of majority rule in two-state interacting spin systems. , 2003, Physical review letters.

[5]  Stefan Klößner,et al.  Opinion Dynamics Under Conformity , 2012 .

[6]  Vincent A. Knight,et al.  On the Peter Principle: An agent based investigation into the consequential effects of social networks and behavioural factors , 2012 .

[7]  Florent Krzakala,et al.  Hiding Quiet Solutions in Random Constraint Satisfaction Problems , 2009, Physical review letters.

[8]  M. Newman,et al.  Nonequilibrium phase transition in the coevolution of networks and opinions. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Serge Galam,et al.  SOCIOPHYSICS: A REVIEW OF GALAM MODELS , 2008, 0803.1800.

[10]  S. Galam.  Social paradoxes of majority rule voting and renormalization group , 1990 .

[11]  Andrea Baronchelli,et al.  Connect and win: The role of social networks in political elections , 2012, ArXiv.

[12]  Alessandro Pluchino,et al.  The Peter Principle Revisited: A Computational Study , 2009, Physica A: Statistical Mechanics and its Applications.

[13]  Kristina Davitt,et al.  Water at the cavitation limit: Density of the metastable liquid and size of the critical bubble , 2010 .

[14]  Katarzyna Sznajd-Weron,et al.  Opinion evolution in closed community , 2000, cond-mat/0101130.

[15]  S. Fortunato,et al.  Statistical physics of social dynamics , 2007, 0710.3256.

[16]  Andre C. R. Martins,et al.  CONTINUOUS OPINIONS AND DISCRETE ACTIONS IN OPINION DYNAMICS PROBLEMS , 2007, 0711.1199.

[17]  K. Sznajd-Weron,et al.  Anticonformity or Independence?—Insights from Statistical Physics , 2013 .

[18]  Katarzyna Sznajd-Weron,et al.  Phase transitions in the q-voter model with two types of stochastic driving. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Steffen Eger,et al.  Opinion Dynamics Under Opposition , 2013, SSRN Electronic Journal.

[20]  Maxi San Miguel,et al.  Ordering dynamics with two non-excluding options: bilingualism in language competition , 2006, physics/0609079.

[21]  S. Galam.  Heterogeneous beliefs, segregation, and extremism in the making of public opinions. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Serge Galam,et al.  Local dynamics vs. social mechanisms: A unifying frame , 2005 .

[23]  Alessandro Pluchino,et al.  Efficient Promotion Strategies in a Hierarchical Organization , 2011, ArXiv.

[24]  S. Redner,et al.  Voter model on heterogeneous graphs. , 2004, Physical review letters.

[25]  S. Galam.  From 2000 Bush–Gore to 2006 Italian elections: voting at fifty-fifty and the contrarian effect , 2007, physics/0703095.

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

[27]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.