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Social network DeGroot model = supporting consensus reaching in opinion dynamics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Social network DeGroot model/ by Yucheng Dong, Zhaogang Ding, Gang Kou.
其他題名:	supporting consensus reaching in opinion dynamics /
作者:	Dong, Yucheng.
其他作者:	Ding, Zhaogang.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xii, 166 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Social networks - Mathematical models. -
電子資源:	https://doi.org/10.1007/978-981-97-0421-7
ISBN:	9789819704217

Social network DeGroot model = supporting consensus reaching in opinion dynamics /
Dong, Yucheng.

Social network DeGroot modelsupporting consensus reaching in opinion dynamics /[electronic resource] :by Yucheng Dong, Zhaogang Ding, Gang Kou. - Singapore :Springer Nature Singapore :2024. - xii, 166 p. :ill. (some col.), digital ;24 cm.

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.

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.

ISBN: 9789819704217

Standard No.: 10.1007/978-981-97-0421-7doiSubjects--Topical Terms:

598894
Social networks
--Mathematical models.

LC Class. No.: HM741

Dewey Class. No.: 302.3015118

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520 $a 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.
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