Binary Opinion Dynamics with Stubborn Agents
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 01, 2013
- Source ID
- 10.1145/2538508
Entities
People
- Amin Saberi
- Anna Scaglione
- Asuman Özdağlar
- Daron Acemoglu
- Ercan Yildiz
Organizations
- Accenture
- Air Force Office of Scientific Research
- Army Research Office
- Division of Computing and Communication Foundations
- Division of Social and Economic Sciences
- Massachusetts Institute of Technology
- Stanford University
- University of California, Davis