Journal ArticleDOI
Binary Opinion Dynamics with Stubborn Agents
Ercan Yildiz,Asuman Ozdaglar,Daron Acemoglu,Amin Saberi,Anna Scaglione +4 more
- Vol. 1, Iss: 4, pp 19
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TLDR
It is shown that the presence of stubborn agents with opposing opinions precludes convergence to consensus; instead, opinions converge in distribution with disagreement and fluctuations.Abstract:
We study binary opinion dynamics in a social network with stubborn agents who influence others but do not change their opinions. We focus on a generalization of the classical voter model by introducing nodes (stubborn agents) that have a fixed state. We show that the presence of stubborn agents with opposing opinions precludes convergence to consensus; instead, opinions converge in distribution with disagreement and fluctuations. In addition to the first moment of this distribution typically studied in the literature, we study the behavior of the second moment in terms of network properties and the opinions and locations of stubborn agents. We also study the problem of optimal placement of stubborn agents where the location of a fixed number of stubborn agents is chosen to have the maximum impact on the long-run expected opinions of agents.read more
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Optimizing Opinions with Stubborn Agents Under Time-Varying Dynamics
D. Scott Hunter,Tauhid Zaman +1 more
TL;DR: It is proved that under fairly general conditions on the stubbornness rates of the individuals, the opinions converge to an equilibrium in the presence of stubborn agents and it is shown that the mean opinion is a monotone submodular function, allowing a good solution using a greedy algorithm.
Proceedings ArticleDOI
Optimizing the coherence of composite networks
Erika Mackin,Stacy Patterson +1 more
TL;DR: This work shows that the coherence of a composite network is a submodular function over the set of potential edges between the disjoint networks, and develops a non-combinatorial algorithm that identifies connecting edges such that the composite network coherence is within a provable bound of optimal.
Posted Content
A Two Phase Investment Game for Competitive Opinion Dynamics in Social Networks
TL;DR: In this article, the authors propose a two-phase opinion dynamics in social networks, where a node's final opinion in the first phase acts as its initial biased opinion for the second phase.
Journal ArticleDOI
Ergodic Opinion Dynamics Over Networks: Learning Influences From Partial Observations
TL;DR: This article proposes a method to estimate the social network topology and the strength of the interconnections starting from partial observations of the interactions, when the whole sample path cannot be observed due to limitations of the observation process.
Journal ArticleDOI
Effects of Time Horizons on Influence Maximization in the Voter Dynamics
TL;DR: This paper analyzes influence maximization in the voter model with an active strategic and a passive influencing party in non-stationary settings and finds that on undirected heterogeneous networks, for short time horizons, influence is maximized when targeting low-degree nodes, while for long timeHorizons influence maximized is achieved when controlling hub nodes.
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