Titlebook: Social Network DeGroot Model; Supporting Consensus Yucheng Dong,Zhaogang Ding,Gang Kou Book 2024 The Editor(s) (if applicable) and The Auth

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,Strategic Manipulations with Trust Relationships,nsensus 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 ch

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,Risk Control in the Evolution of Public Opinion,evelop 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 dev

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,Social Network DeGroot Model in Uncertain Contexts,over, 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

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,Risk Control in the Evolution of Public Opinion,ents 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.

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,Social Network DeGroot Model in Uncertain Contexts,. 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.

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https://doi.org/10.1007/978-981-97-0421-7Opinion Dynamics; Social Networks; DeGroot Model; Consensus; Group Decision Making; Convergence Speed; Str

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,Social Network DeGroot Model: Consensus and Convergence Speed,This chapter presents the social network DeGroot (SNDG) model. Subsequently, we propose the consensus condition, weights and convergence speed in SNDG.