Overview
- Nominated as an outstanding PhD thesis by The Australian National University, Canberra, Australia
- Advances the modeling and understanding of how individuals’ opinions evolve in a social network
- Accessible for an inter-disciplinary audience of social scientists and engineers
Part of the book series: Springer Theses (Springer Theses)
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Table of contents (10 chapters)
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Front Matter
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How Differences in Private and Expressed Opinions Arise
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Front Matter
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Evolution of Individual Social Power
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Front Matter
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Opinion Dynamics with Interdependent Topics
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Front Matter
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Back Matter
Keywords
- Social Networks Analysis
- Influence Networks
- Evolution of Social Power
- Degroot Model
- Friedkin–Johnsen Model
- Continuous-Time Model
- Agent-Based Opinion Dynamics
- Expressed–Private–Opinion Model
- Opinion Dynamics on Interdependent Topics
- Discrepancy between Private and Expressed Opinions
- Pluralistic Ignorance in Social Networks
- Asch’s Conformity Experiments
- Preference Falsification
- Consensus of Autonomous Agents
- complexity
About this book
This book uses rigorous mathematical analysis to advance opinion dynamics models for social networks in three major directions. First, a novel model is proposed to capture how a discrepancy between an individual’s private and expressed opinions can develop due to social pressures that arise in group situations or through extremists deliberately shaping public opinion. Detailed theoretical analysis of the final opinion distribution is followed by use of the model to study Asch’s seminal experiments on conformity, and the phenomenon of pluralistic ignorance. Second, the DeGroot-Friedkin model for evolution of an individual’s social power (self-confidence) is developed in a number of directions. The key result establishes that an individual’s initial social power is forgotten exponentially fast, even when the network changes over time; eventually, an individual’s social power depends only on the (changing) network structure. Last, a model for the simultaneous discussion of multiple logically interdependent topics is proposed. To ensure that a consensus across the opinions of all individuals is achieved, it turns out that the interpersonal interactions must be weaker than an individual’s introspective cognitive process for establishing logical consistency among the topics. Otherwise, the individual may experience cognitive overload and the opinion system becomes unstable. Conclusions of interest to control engineers, social scientists, and researchers from other relevant disciplines are discussed throughout the thesis with support from both social science and control literature.
Authors and Affiliations
Bibliographic Information
Book Title: Opinion Dynamics and the Evolution of Social Power in Social Networks
Authors: Mengbin Ye
Series Title: Springer Theses
DOI: https://doi.org/10.1007/978-3-030-10606-5
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-10605-8Published: 01 March 2019
eBook ISBN: 978-3-030-10606-5Published: 19 February 2019
Series ISSN: 2190-5053
Series E-ISSN: 2190-5061
Edition Number: 1
Number of Pages: XXIII, 209
Number of Illustrations: 2 b/w illustrations, 51 illustrations in colour
Topics: Control and Systems Theory, Media Sociology, Complexity, Graph Theory