| 张楠,杨洁.自然灾害网络舆情风险评估与预警研究[J].情报工程,2026,(3):035-045 |
| 自然灾害网络舆情风险评估与预警研究 |
| Natural Disaster Network Public Opinion Risk Assessment and Early Warning |
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| DOI: |
| 中文关键词: 自然灾害网络舆情;风险评估;预警;熵权-TOPSIS;SSA-BP 神经网络 |
| 英文关键词: Natural Disaster Online Public Opinion; Risk Early Warning; Entropy Weight-TOPSIS; SSA-BP Neural Network |
| 基金项目:国家社会科学基金项目“黑龙江沿岸世居民族传统物候历研究”(22BMZ074);黑龙江省哲学社会科学规划项目“黑龙江省国家级非遗可视化设计研究”(23YSD245);黑龙江省属高等学校基础科研业务费项目“工业网络流量异常检测研究”(2024-KYYWF-1099)。 |
| 作者 | 单位 | | 张楠 | 哈尔滨商业大学经济学院 哈尔滨 150028 | | 杨洁 | 哈尔滨商业大学经济学院 哈尔滨 150028 |
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| 中文摘要: |
| [目的/意义]自然灾害事件网络舆情不仅影响受灾地区的人民群众,还对社会稳定、政府形象以及网络生态造成深远的影响,及时对自然灾害网络舆情进行风险评估和预警对于维护社会稳定和公共安全至关重要。[方法/过程]在详细分析自然灾害网络舆情的影响因素下,选取舆情本体、舆情主体、舆情客体等三个维度建立风险评估指标体系,在详细分析自然灾害网络舆情影响因素的基础上,熵值法TOPSIS计算舆情事件的风险权重和风险指数,并构建BP 神经网络和基于麻雀搜索算法优化的BP(SSA-BP)神经网络预警模型。[结果/结论]研究结果表明,利用本文构建的自然灾害网络舆情模型能够准确评估并预警不同级别的舆情风险,为政府部门和应急管理机构提供有价值的决策支持。 |
| 英文摘要: |
| [Purpose/Significance] The online public opinion of natural disaster events not only affects the people in the affected areas, but also has a far-reaching impact on social stability, government image and network ecology. Timely risk assessment and early warning of online public opinion of natural disaster are crucial to maintaining social stability and public safety. [Method/Process] Based on the detailed analysis of the influencing factors of online public opinion of natural disasters, the risk assessment index system was constructed by selecting public opinion ontology, public opinion subject and public opinion object from three dimensions. Correlation and principal component analysis were used to screen the indicators, and the risk weight and risk index of public opinion events are calculated by combining the approximation ideal solution ranking method based on the entropy weight method (entropy weight-TOPSIS method). The network warning models of BP and BP Neural Network optimized by Sparrow Search Algorithm (SSA-BP neural network) were constructed. [Result/Conclusion] The research results show that the natural disaster network public opinion model constructed in this paper can accurately assess and warn public opinion risks at different levels, providing valuable decision support for government departments and emergency management agencies. |
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