The internet often serves as a communication platform for users to freely express opinions. However, as it supports the quick and wide spread of public opinions, it often results in great uncertainty and is very difficult to control. As a result, evaluating the risk levels of internet public opinion becomes very challenging. The safety of internet public opinion affects the sustainability and stability of society. In this paper, a novel conceptual model of internet public opinion governance is proposed. The model can be used to grade risk levels by combining the Analytic Hierarchy Process Sort II (AHPSort II) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) under a fuzzy environment with triangular fuzzy sets. A numerical example is provided to verify the efficiency of the proposed method, and some managerial implications are also discussed.

Purpose: The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station. Design/methodology/approach: The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced. Findings: The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation. Originality/value: The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.