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Social Network DeGroot Model: Supporting Consensus Reaching in Opinion Dynamics

Autor Yucheng Dong, Zhaogang Ding, Gang Kou
en Limba Engleză Hardback – 28 apr 2024
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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Specificații

ISBN-13: 9789819704200
ISBN-10: 9819704200
Pagini: 210
Ilustrații: XII, 166 p. 64 illus., 38 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.45 kg
Ediția:2024
Editura: Springer Nature Singapore
Colecția Springer
Locul publicării:Singapore, Singapore

Cuprins

Chapter 1. Introduction.- Chapter 2. Social Network DeGroot Model: Consensus and convergence speed.- Chapter 3. Consensus reaching through adding minimum interactions.- Chapter 4. Strategic Manipulations with trust relationships.- Chapter 5. Risk control in the evolution of public opinions.- Chapter 6. Social Network DeGroot Model in uncertain contexts.

Notă biografică

Yucheng Dong received the B.S. and M.S. degrees in mathematics from Chongqing University, Chongqing, China, in 2002 and 2004, respectively, and the Ph.D. degree in management from Xi’an Jiaotong University, Xi’an, China, in 2008. He is currently a Professor with the Business School, Sichuan University, Chengdu, China. He has authored or coauthored more than 200 international journal papers in some refereed journals. He won the 2021 Clemen-Kleinmuntz Decision Analysis Best Paper Award (INFORMS) and 2022 IEEE
TFS Outstanding Paper Award (IEEE CIS). His current research interests include decision analysis and human dynamics. Prof. Dong is an Area Editor/Associate Editor of Computers and Industrial Engineering, Group Decision and Negotiation, IEEE Transactions on Artificial Intelligence, IEEE Transactions on Systems, Man, and Cybernetics: Systems, and Information Fusion. He has been identified by Clarivate as a Highly Cited Researcher in the two fields of computer science and engineering. Zhaogang Ding is currently an Associate professor at the School of Public Management (Emergency Management), Northwest University, China. He received his Ph.D. degree in
Management Science from Sichuan University in 2017. His research interests include opinion dynamics and social network analysis. He has published several international journal papers in IEEE Transactions on Big Data, IEEE Transactions on Computational Social Systems, Information Sciences, Journal of Artificial Societies and Social Simulation, among others.
Gang Kou is a Distinguished Professor of Chang Jiang Scholars Program in Southwestern University of Finance and Economics, managing editor of International Journal of Information Technology & Decision Making, and managing editor-in-chief of Financial Innovation. He is also editors for the following journals: Decision Support Systems, European Journal of Operational Research, Technological and Economic Development of Economy. Previously, he was a professor of School of Management and Economics, University of Electronic Science and Technology of China, and a research scientist in Thomson Co., R&D. He received his Ph.D. in Information Technology from the College of Information Science & Technology, Univ. of Nebraska at Omaha; Master degree i n Dept of Computer Science, Univ. of Nebraska at Omaha; and B.S. degree in Department of Physics, Tsinghua University, China. He has published more than 100 papers in various peer-reviewed journals

Textul de pe ultima copertă

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 results reported 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.

Caracteristici

Connect opinion dynamics, social network, and group decision making Manages consensus process and strategic manipulations in group decision making Presents new tools for understanding the evolution of public opinion in social networks