面向互联网舆情事件的企业风险识别——基于KGANN模型  

Enterprise Risk Identification for Internet Public Opinion Events——Based on KGANN Model

作　　者：张志剑 刘政昊 马费成[1,2,3] ZHANG Zhi-jian;LIU Zheng-hao;MA Fei-cheng(School of Information Management,Wuhan University,Wuhan 430072,China;Institute of Big Data,Wuhan University,Wuhan 430072,China;Center for Studies of Information Resources,Wuhan University,Wuhan 430072,China)

机构地区：[1]武汉大学信息管理学院,湖北武汉430072 [2]武汉大学大数据研究院,湖北武汉430072 [3]武汉大学信息资源研究中心,湖北武汉430072

出　　处：《工程管理科技前沿》2022年第1期65-73,共9页Frontiers of Science and Technology of Engineering Management

基　　金：国家自然科学基金资助项目(91646206);科技创新2030“新一代人工智能”重大基金资助项目(2020AAA0108505)。

摘　　要：信息智能时代背景下,互联网舆情信息对企业的影响愈加显著。有效准确地从舆情事件中识别风险有助于企业进行风险管理,实现良性运营。本文提出一种有效识别企业风险的模型KGANN,该模型使用知识图谱的结构和内容构造神经网络,实现知识图谱和神经网络的融合,从而提升模型风险识别能力。实验结果表明,在企业风险识别任务上所提方法相较于传统方法具有显著优势。同时根据知识的权重值对模型进行分析,得到股权结构复杂、司法案件较多、知识产权较少的企业风险等级较高。研究结果为企业和监管机构进行风险管理提供了重要的研究视角,对防范企业风险具有一定的参考价值。Under the background of the information intelligence era,the impact of Internet public opinion information on enterprises is becoming more and more significant.Effectively and accurately identifying risks from public opinion events is helpful for enterprises to carry out risk management and realize benign operations.This paper proposes a model KGANN for effectively identifying enterprise risk.The model uses the structure and content of knowledge graph to construct a neural network to realize the integration of knowledge graph and neural network to improve the ability of model risk identification.The experimental results show that the proposed method has significant advantages over the traditional methods in enterprise risk identification.At the same time,the model is analyzed according to the weight value of knowledge.It is concluded that the enterprise with a complex ownership structure,more judicial cases,and less intellectual property rights has a higher risk level.The research results provide an essential research perspective for enterprises and regulators to carry out risk management and have a specific reference value for preventing enterprise risks.

关 键 词：互联网舆情 风险识别 风险事件 知识图谱 神经网络 

分 类 号：F272.35[经济管理—企业管理]