A Multi-Step Interaction Opinion Dynamics Group Decision-Making Method and Its Application in Art Evaluation

A Multi-Step Interaction Opinion Dynamics Group Decision-Making Method and Its Application in Art Evaluation

Yingtian Li
Copyright: © 2023 |Pages: 14
DOI: 10.4018/IJFSA.320485
Article PDF Download
Open access articles are freely available for download
Add to Your Personal Library: Article


Due to the development of intelligent decision-making, social network group decision making (SNGDM) has become increasingly valued. Self-persistence is a significant topic in SNGDM problems, while it is ignored in most existing research. Besides, existing opinion evolution models often ignore high-order interactions because they assume individuals only communicate with their friends or neighbors. With these issues in mind, the authors propose a multi-step interaction opinion dynamics model to manage the consensus in SNGDM problem with self-persistence evolution. Given the decision makers' social network information, the centrality degree, interaction strength, and high-order interactions are combined to construct a social influence network. Inspired by the social influence model, the authors develop an opinion dynamic consensus model which also describes the evolution of self-persistence in a group of decision makers. Finally, an example and detailed simulation experiment are presented to demonstrate the efficiency of the proposed consensus model.
Article Preview

1 Introduction

Group decision making (GDM) can be regarded as a powerful tool to select the most desirable alternatives in the situation where a group of decision makers (DMs) participate to achieve a common solution (Bezdek, 1978) and has been applied in various fields (García-Zamora, 2022; Li, Liu & Li, 2021, 2022; Yu & Li 2022; Yu, Fei & Li 2019). The development of the economy and web technologies pushes GDM problem to more complex situations. Consequently, social network group decision making (SNGDM) problem is becoming an important topic and gaining popularity in the decision making field (Gong, Wang, Guo, Gong & Wei, 2020; Wang, Liang & Li, 2022; Liao, & Liu, 2017; Li, Rodríguez & Wei, 2021). But this situation also brings new challenges, such as effective social network information supervision and difficulties of reaching consensus, etc. Reaching consensus is very important in GDM problems, because it can increase the efficiency in the implementation of the obtained decision (Palomares, Estrella, Martínez & Herrera, 2014; Quesada, Palomares & Martínez, 2015; Rodríguez, Labella, Tré & Martínez, 2018; Yu, Li & Fei, 2018; Zuo, Li & Yu, 2020). It is usually very difficult to achieve a common solution accepted by all DMs.

Studies on consensus model of SNGDM are still in the inceptive stage with only a small amount of researches (Ding, Wang, Shang & Herrera, 2019; Liu, Zhou, Ding & Palomares, 2019; Liang, Guo & Liu, 2022, Zuo, Li & Yu 2020). Notably, there are mainly two types of model based on social network (Dong, Zhan, Kou, Fujita, Chiclana & Herrera-Viedma, 2018), the one is based on trust relationship (Wu, Chiclana, Fujita, & Herrera-Viedma, 2017; Zhang, Wang, Dong, Chiclana & Herrera-Viedma, 2022; Wu, Zhang, Liu & Cao, 2019) and the other one is based on opinion evolution (Capuano, Chiclana, Fujta, Herrera-Viedma & Loia, 2018; Dong, Ding, Martínez & Herrera, 2017). As for the former one, for instance, Wu, Chang, Cao, & Liang (2019) and Wu, Chiclana, Fujita & Herrera-Viedma (2017) studied the trust propagation approaches and developed some consensus models based on the trust relationship between DMs. Ding, Wang, Shang & Herrera (2019) developed a social network analysis-based conflict relationship investigation process and a conflict degree-based consensus reaching process (CRP) for GDM problems. Wu, Zhang, Liu & Cao (2019) utilized a network partition algorithm based on trust relationship to reduce the complexity of GDM problem and then the weights of independent sub-networks and their individual members are computed by their trust values. Liu, Zhou, Ding & Palomares (2019) proposed a model considering both the preference inconformity and the relationship disharmony to detect and eliminate the conflict for GDM in social network context. Zhang, Iván, Dong & Wang (2019) defined some principles to detect the DMs' non-cooperative behaviors, and then social network analysis was used for the non-cooperative behavior management.

Complete Article List

Search this Journal:
Volume 12: 1 Issue (2023)
Volume 11: 4 Issues (2022)
Volume 10: 4 Issues (2021)
Volume 9: 4 Issues (2020)
Volume 8: 4 Issues (2019)
Volume 7: 4 Issues (2018)
Volume 6: 4 Issues (2017)
Volume 5: 4 Issues (2016)
Volume 4: 4 Issues (2015)
Volume 3: 4 Issues (2013)
Volume 2: 4 Issues (2012)
Volume 1: 4 Issues (2011)
View Complete Journal Contents Listing