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
Reads0
Chats0
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
Citations
More filters
Journal ArticleDOI
Opinion diffusion on multilayer social networks
TL;DR: This paper characterizes the influence of multilayer network topology and agent attribute on opinion diffusion in a holistic way, but also demonstrates the importance of coupling agents which play an indispensable role in some social and economic situations.
Journal ArticleDOI
When is Society Susceptible to Manipulation
TL;DR: In this article, the authors consider a social learning model where agents learn about an underlying state of the world from individual observations as well as from exchanging information with each other, and derive conditions under which a social network is impervious and cannot be manipulated.
Posted Content
Optimal Multiphase Investment Strategies for Influencing Opinions in a Social Network
TL;DR: In this article, the authors study the problem of optimally investing in nodes of a social network in a competitive setting, where two camps aim to maximize adoption of their opinions by the population.
Journal ArticleDOI
Voter and Majority Dynamics with Biased and Stubborn Agents
TL;DR: In this paper, the authors study binary opinion dynamics in a fully connected network of interacting agents and show that consensus can be achieved on the preferred opinion with high probability even if it is initially the opinion of the minority.
Proceedings Article
Shaping Opinion Dynamics in Social Networks
TL;DR: Experiments on several synthetic and real datasets gathered from Twitter show that SmartShape can accurately determine the quality of a set of control users as well as shape the opinion dynamics more effectively than several baselines.
References
More filters
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.