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[目的/意义]研究网络舆情语义倾向性隶属度,增强对网络舆情研判与引导的科学化程度,为相关部门提供决策参考。[方法/过程]在探讨网络舆情语义识别的基础上,运用模糊数学方法对网络舆情信息语义倾向性隶属度进行相关研究,并结合具体实证展开分析。[结果/结论]实验结果表明,本文所提出的算法能够深入挖掘网络舆情语义倾向性信息,更好地为相关管理者提供舆情危机预警服务,提高决策效率。
[Purpose / Significance] To study the semantic orientation affiliation of network public opinion, to enhance the scientific degree of network public opinion judgment and guidance, and to provide relevant departments with decision-making reference. [Methods / Processes] On the basis of exploring the semantic recognition of Internet public opinion, this paper uses the fuzzy mathematics method to study the semantic orientation affiliation of online public opinion information, and analyzes it with the concrete examples. [Result / Conclusion] The experimental results show that the proposed algorithm can dig deep semantic information of network public opinion, provide early warning service of public opinion crisis to related managers and improve decision efficiency.