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Social Network DeGroot Model

Supporting Consensus Reaching in Opinion Dynamics

verfasst von: Yucheng Dong, Zhaogang Ding, Gang Kou

Verlag: Springer Nature Singapore

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book investigates the DeGroot model in social network contexts, and proposes the social network DeGroot (SNDG) model. Specifically, this book focuses on two core research problems in the SNDG model: (i) Social network structures to reach a stable state (consensus, polarization, or fragmentation); and (ii) the convergence rate to reach a stable state. Furthermore, the authors generalize the SNDG model in an uncertain context, showing the effects of interval opinions on the SNDG model. In this book, the authors also discuss the applications of the SNDG model to support group decision making, including consensus reaching through adding minimum interactions, trust relationships manipulations, and risk control issues in the social network. Apart from theoretical analysis, detailed experimental simulations with real and random data will be applied to validate our research.

This book is the first to connect opinion dynamics, social network and group decision making. The resultsreported can help us understand the evolution of public opinions in social network contexts and provide new tools to support consensus reaching in group decision making.

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Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract

In this chapter, we introduce the basic concepts and several basic models of opinion dynamics. In particular, we present the DeGroot model and its desired properties. Subsequently, we introduce group decision-making (GDM) and consensus-reaching process (CRP). Then, we provide the basic concepts regarding the graph, matrix, and social simulation to aid readers in understanding the proposals in this book. Finally, we provide a chapter overview to demonstrate the structure of this book.

Yucheng Dong, Zhaogang Ding, Gang Kou

Chapter 2. Social Network DeGroot Model: Consensus and Convergence Speed

Abstract

This chapter presents the social network DeGroot (SNDG) model. Subsequently, we propose the consensus condition, weights and convergence speed in SNDG.

Yucheng Dong, Zhaogang Ding, Gang Kou

Chapter 3. Consensus Reaching Through Adding Minimum Interactions

Abstract

In this chapter, we consider the optimization-based consensus model to reach a consensus by adding minimum interactions in the SNDG model. Then, we propose algorithms to obtain the optimal solution using two steps: network partition and edge addition. Furthermore, we extend the optimization-based consensus model to manage the consensus with an established target. Finally, we provide numerical analysis to aid in understanding the optimization-based consensus model in the SNDG model.

Yucheng Dong, Zhaogang Ding, Gang Kou

Chapter 4. Strategic Manipulations with Trust Relationships

Abstract

This chapter presents a trust relationship consensus reaching process (CRP) with a feedback mechanism that consists of two approaches to facilitate consensus reaching: (1) the leader-based preference adjustment and (2) the trust relationships improvement. We establish a bridge between opinion dynamics and group decision-making (GDM) in the trust relationships CRP to highlight the importance of leaders and trust relationship improvements in GDM challenges. Furthermore, we present a new strategic manipulation issue, trust relationship manipulation, and discuss some clique-based strategies to manipulate trust relationships and obtain the desired ranking of the alternatives in GDM challenges. Finally, detailed simulation experiments are proposed to justify our proposal.

Yucheng Dong, Zhaogang Ding, Gang Kou

Chapter 5. Risk Control in the Evolution of Public Opinion

Abstract

The evolution of opinion in Internet social networks may result in several risk issues in digital era, which have garnered government attention, and develop in business. This chapter proposes an index to measure the risk level in opinion evolution within the framework of the SNDG model and then presents the upper and lower bounds of risks determined by the social network structures. Furthermore, the social network risk control (SNRC) model is developed to control risk evolution by adding minimum interactions; some desired properties of the SNRC model are presented and discussed.

Yucheng Dong, Zhaogang Ding, Gang Kou

Chapter 6. Social Network DeGroot Model in Uncertain Contexts

Abstract

When people state their opinions, they often cannot provide exact opinions but express uncertainty, such as an opinion within numerical interval. Moreover, owing to the differences in the cultural background and character of agents, people who encounter numerical interval opinions often exhibit different uncertainty tolerances. By considering different numerical interval opinions and uncertainty tolerances, in this chapter, we propose a numerical interval opinion dynamics model to investigate the process of forming collective opinions in a group of interaction agents under an uncertain context. We propose the theoretical analysis and algorithms to identify the stable agents whose opinions will become stable and the oscillation agents whose opinions will always fluctuate in the opinion evolution process.

Yucheng Dong, Zhaogang Ding, Gang Kou

Titel: Social Network DeGroot Model
verfasst von: Yucheng Dong
Zhaogang Ding
Gang Kou
Copyright-Jahr: 2024
Verlag: Springer Nature Singapore
Electronic ISBN: 978-981-9704-21-7
Print ISBN: 978-981-9704-20-0
DOI: https://doi.org/10.1007/978-981-97-0421-7

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