Risk perception and intelligent decision in complex social information network

Purpose: The increase of turbulence sources and risk points under the complex social information network has brought severe challenges. This paper discusses risk perception and intelligent decision-making under the complex social information network to maintain social security and financial security. Design/methodology/approach: Cross-modal semantic fusion and social risk perception, temporal knowledge graph and analysis, complex social network intelligent decision-making methods have been studied. A big data computing platform of software and hardware integration for security combat is constructed based on the technical support. Findings: The software and hardware integration platform driven by big data can realize joint identification of significant risks, intelligent analysis and large-scale group decision-making. Practical implications: The integrated platform can monitor the abnormal operation and potential associated risks of Listed Companies in real-time, reduce information asymmetry and accounting costs and improve the capital market's ability to serve the real economy. It can also provide critical technical support and decision support in necessary public opinion monitoring and control business. Originality/value: In this paper, the theory of knowledge-enhanced multi-modal multi-granularity dynamic risk analysis and intelligent group decision-making and the idea of an inference think tank (I-aid-S) is proposed. New technologies and methods, such as association analysis, time series evolution and super large-scale group decision-making, have been established. It's also applied in behavior and situation deduction, public opinion and finance and provides real-time, dynamic, fast and high-quality think tank services.