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Journal ArticleDOI

Binary Opinion Dynamics with Stubborn Agents

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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.

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Citations
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Journal ArticleDOI

Transmission errors and influence maximization in the voter model

TL;DR: The effects of mistakes in opinion propagation in the voter model on strategic influence maximization are analyzed and it is found that the regime of optimal hub control is the larger, the more heterogeneous the social network and the smaller the more resources both available to the influencers.
Proceedings ArticleDOI

Performance Analysis of Online Social Platforms

TL;DR: In this paper, an original mathematical model to analyze the diffusion of posts within a generic online social platform is introduced, which takes into account not only the social graph structure, but also the platform design, user activity (self-and re-posting), as well as competition among posts.
Posted Content

On a Modified DeGroot-Friedkin Model of Opinion Dynamics

TL;DR: It is shown that for the modified model, the vector of individuals' self-confidence levels converges to a unique nontrivial equilibrium which for each individual is equal to 1 over n, where n is the number of individuals and implies that eventually individuals reach a democratic state.
Journal ArticleDOI

Forecasting elections results via the voter model with stubborn nodes

TL;DR: A novel method to forecast the result of elections using only official results of previous ones is proposed, based on the voter model with stubborn nodes and uses theoretical results developed in a previous work of the authors'.
Journal ArticleDOI

A bistable belief dynamics model for radicalization within sectarian conflict

TL;DR: In this article, a two-variable model to describe spatial polarization, radicalization, and conflict is introduced, where individuals harbor a continuous belief variable as well as a discrete radicalization level expressing their tolerance to neighbors with different beliefs.
References
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Journal ArticleDOI

A Simple Model of Herd Behavior

TL;DR: In this article, the authors analyze a sequential decision model in which each decision maker looks at the decisions made by previous decision makers in taking her own decision, and they show that the decision rules that are chosen by optimizing individuals will be characterized by herd behavior.
Proceedings ArticleDOI

Maximizing the spread of influence through a social network

TL;DR: An analysis framework based on submodular functions shows that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models, and suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.
Journal ArticleDOI

A New Product Growth for Model Consumer Durables

TL;DR: A growth model for the timing of initial purchase of new products is developed and tested empirically against data for eleven consumer durables, and a long-range forecast is developed for the sales of color television sets.
Journal ArticleDOI

Maximizing the Spread of Influence through a Social Network

TL;DR: The problem of finding the most influential nodes in a social network is NP-hard as mentioned in this paper, and the first provable approximation guarantees for efficient algorithms were provided by Domingos et al. using an analysis framework based on submodular functions.
Book

Interacting Particle Systems

TL;DR: The construction, and other general results are given in this paper, with values in [0, ] s. The voter model, the contact process, the nearest-particle system, and the exclusion process.
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