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In recent years, major emergencies occurred more and more frequently in China, the types and frequency of disasters have increased obviously, and the scope of involvement has expanded markedly, such as “the explosion accident in Tianjin Binhai New Area on August 12, 2015,” “the heavy rainstorm in Zhengzhou on July 20, 2021,” and “the Corona Virus Disease on December, 2019,” etc. The high complexity and destructive nature of major emergencies have a huge negative impact on the social order, economic development, and people's lives and properties in China (Guo et al., 2020; Tan et al., 2021; Wu et al., 2021b). The primary task after a major emergency is to organize experts analyze and judge the current state of affairs, strive to make scientific and efficient decisions quickly in a short period, control the development of events as possible and reduce the loss or consumption of resources caused or likely to be caused due to the emergency. Therefore, there is an urgent need for the support of group decision-making methods (Cao et al., 2022; Wu et al., 2020; Wu et al., 2021a). The complexity and variability of mega-emergency events determine that emergency decision-making requires the participation of multiple experts from different fields, which makes the emergency decision-making characterized by complex large-group decision-making, and the traditional group decision-making methods are no longer applicable to such decision-making problems. Various LGEDM methods have been proposed successively (Xu et al., 2015; Xu et al., 2017). Compared with traditional group decision problems, the LGEDM usually involve more than 20 decision makers with the characteristics of time constraint, decision environment uncertainty, decision information limitation, and the possibility of catastrophic loss due to decision errors (Tang et al., 2020; Xing et al., 2022; Wu et al., 2022).
With the development of information technology, the Internet has become a huge platform for the expression of public opinion, and events are fermented very fast on the Internet. Once the emergency breaks out, hundreds of millions of netizens gather and participate in it rapidly, posting related comments on social media platforms, thus generating massive text data. This textual information not only reflects the public's concern about the emergencies but also provides important references for emergency decision-makers. Therefore, in the process of emergency decision-making, how to effectively utilize the public views in social media and express and integrate the decision information of large groups efficiently under urgent time pressure, is one of the pressing problems in the field of emergency decision-making. At present, the research of the LGEDM method under a big data environment has shown initial results in the field of decision making (Xu et al., 2019b; Xu et al., 2019c). In addition, the complexity, dynamics, and urgency of LGEDM problems also imply that more uncertainties are bound to appear in the decision-making process, which we call risk. If these risks cannot be controlled within the effective range, they will become new risk sources, which will further deteriorate the situation and lead to low quality or failure of decision-making. Therefore, introducing decision risk into LGEDM is one of the main methods for ensuring decision reliability, which has attracted a worldwide interest (Yin et al., 2021; Zhong et al., 2020). But in general, the related research is still in the initial stage.