Abstract
Experimental and field research has demonstrated a pervasive tendency toward pairwise conformity among individuals connected by positive social ties, and work using formal models has shown that opinions on connected influence networks should thus converge toward uniformity. Observing that diversity persists even in small scale groups and organizations, we investigate two empirically grounded mechanisms of social differentiation that may account for this persistence: First, actors may dislike or disrespect peers who diverge too much from their own views, and may change their opinions or behaviors to distance themselves further from those negative referents. Second, when surrounded by similar others, actors may try to maintain a sufficient sense of uniqueness by exploring new opinions or behaviors. Using computational experiments, we demonstrate that these two mechanisms lead to different patterns of polarization, radicalization, and factionalism and also investigate the conditions under which integration occurs. In closing, we discuss the implications for cultural dynamics in organizations.
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Notes
- 1.
Digital computers may fail to distinguish very small numbers from zero (Izquierdo and Polhill 2006), an error that would be consequential here in that it would erase the distinction between weak influence and no influence. To avoid such problems with floating point inaccuracy, we assign a minimum on positive weights at 10−5 and assign a maximum on negative weights at \(-1{0}^{-5}\). We thus conservatively ensure that weak ties are not mistakenly treated as null ties by the computer.
- 2.
It is commonly believed that positive influence models invariably produce consensus on connected networks. Even as we add that the network must be strongly connected (i.e. paths allow influence to flow in both directions for all dyads in the population), this may not be strictly true in discrete time for certain network structures if the influence weight is high enough. The lack of convergence is obvious if influence weights (w ij, t ) are allowed to exceed 1. 0, of course, but even w ij, t = 1 will yield stable limit cycles that prevent convergence for certain network structures. See Kitts and Trowbridge (2007) for an explanation of the general problem. This is not a danger here because influence weights in our model are strictly determined by similarity; that is, if w ij, t = 1 then the agents’ opinions are already identical and no influence is possible. Thus stable limit cycles cannot prevent convergence.
- 3.
We show below that the model may in this condition generate multiplex equilibria, where two extreme factions are accompanied by moderate subgroups. While interesting, these outcomes are very rare and vanish in the presence of noise.
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Acknowledgements
The research of Andreas Flache and Michael Mäs has been supported by the Netherlands Organization for Scientific Research, NWO (VIDI Grant 452-04-351). James Kitts acknowledges support from the National Science Foundation (BCS-0433086 and IIS-0433637).
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Mäs, M., Flache, A., Kitts, J.A. (2014). Cultural Integration and Differentiation in Groups and Organizations. In: Dignum, V., Dignum, F. (eds) Perspectives on Culture and Agent-based Simulations. Studies in the Philosophy of Sociality, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-319-01952-9_5
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