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    Formulating opinion dynamics from belief formation, diffusion and updating in social network group decision-making: Towards developing a holistic framework

    Wen, Tao, Zheng, Rui, Wu, Ting, Liu, Zeyi, Zhou, Mi, Abbas Syed, Tahir, Ghataoura, Darminder and Chen, Yuwang (2024) Formulating opinion dynamics from belief formation, diffusion and updating in social network group decision-making: Towards developing a holistic framework. European Journal of Operational Research. ISSN 0377-2217

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    Abstract

    Interactions in social networks have become an integral part of people’s daily lives. In various decision-making situations, individuals usually hold diverse prior beliefs and engage in communication with their social connections to make informed decisions. However, most existing research focuses on isolated steps of this process, overlooking the overall complexity of decision-making in social networks. To bridge this important research gap, our paper aims to explore the key steps involved in the process and develop a holistic framework for analyzing how individuals form, exchange and update beliefs, ultimately leading to opinion dynamics and group decision behaviors in a social network. Specifically, relevant literature that focuses on different steps will be reviewed and drawn together to characterize the decision-making process in a comprehensive and systematic manner: individuals form initial beliefs following the principle of multiple criteria decision-making intuitively, information propagates in the social network and affects individuals’ beliefs differently in a form of social influence, beliefs evolve through dynamic interactions with others, and eventually individuals make their decisions, leading to group decision behaviors in the social network. Applications will be briefly discussed to illustrate the practical implications of this research. Finally, conclusions and future research outlook will be discussed in detail. It is expected that the holistic framework developed on the basis of the comprehensive literature review can provide in-depth insights into decision analysis in social networks and shed light on future research and applications toward effective integration of decision science, operational research, and social network analysis.

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