Opinion Dynamics in Networks: Convergence, Stability and Lack of Explosion

Authors Tung Mai, Ioannis Panageas, Vijay V. Vazirani

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Tung Mai
Ioannis Panageas
Vijay V. Vazirani

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Tung Mai, Ioannis Panageas, and Vijay V. Vazirani. Opinion Dynamics in Networks: Convergence, Stability and Lack of Explosion. In 44th International Colloquium on Automata, Languages, and Programming (ICALP 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 80, pp. 140:1-140:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


Inspired by the work of Kempe et al. [Kempe, Kleinberg, Oren, Slivkins, EC 2013], we introduce and analyze a model on opinion formation; the update rule of our dynamics is a simplified version of that of [Kempe, Kleinberg, Oren, Slivkins, EC 2013]. We assume that the population is partitioned into types whose interaction pattern is specified by a graph. Interaction leads to population mass moving from types of smaller mass to those of bigger mass. We show that starting uniformly at random over all population vectors on the simplex, our dynamics converges point-wise with probability one to an independent set. This settles an open problem of [Kempe, Kleinberg, Oren, Slivkins, EC 2013], as applicable to our dynamics. We believe that our techniques can be used to settle the open problem for the Kempe et al. dynamics as well. Next, we extend the model of Kempe et al. by introducing the notion of birth and death of types, with the interaction graph evolving appropriately. Birth of types is determined by a Bernoulli process and types die when their population mass is less than epsilon (a parameter). We show that if the births are infrequent, then there are long periods of "stability" in which there is no population mass that moves. Finally we show that even if births are frequent and "stability" is not attained, the total number of types does not explode: it remains logarithmic in 1/epsilon.
  • Opinion Dynamics
  • Convergence
  • Jacobian
  • Center-stable Manifold


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