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非洲猪瘟舆情信息对我国猪肉价格波动影响的研究
Study on the Influence of Public Opinion Information of the African Swine Fever on the Fluctuation of Pork Prices in China

DOI: 10.12677/HJDM.2022.121007, PP. 49-72

Keywords: 舆情指数,文本挖掘,VAR模型,空间自相关,聚类分析
Public Opinion Index
, Text Mining, VAR Model, Spatial Autocorrelation, Cluster Analysis

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Abstract:

非洲猪瘟自2018年8月爆发以来,对我国生猪产业和人民生活带来了重大的影响。为了实现猪瘟舆情的量化以及研究非洲猪瘟舆情与猪价的传导关系,以及猪价空间分布情况。本文利用从LDA主题模型,支持向量机、随机森林、梯度下降等机器学习构造情感分类器,TF-IDF计算特征词权重加权计算出非洲猪瘟舆情指数,并通过VAR模型研究舆情指数与猪价的传导关系,最后再利用空间自相关分析方法分析猪价的省域特征,并用聚类分析加以验证。本文丰富了非洲猪瘟舆情分析的研究方法,并首次将舆情的文本处理方法应用于猪瘟舆情分析,为国内相关企业和政府对于生猪的生产调控和猪肉定价等提供了参考意见。
Since the outbreak of the African Swine Fever in August 2018, it has had a significant impact on my country’s pig industry and people’s lives. In order to quantify the public opinion of swine fever and study the conduction relationship between the public opinion of African swine fever and the prices of pigs, as well as the spatial distribution of pig prices. This paper uses machine learning from the LDA topic model, support vector machine, random forest, gradient descent to construct sentiment classifier, uses TF-IDF to calculate the weight of feature words to calculate the African swine fever public opinion index, and uses the VAR model to study the conduction relationship between the public opinion index and pig prices. Finally, the spatial autocorrelation analysis method is used to analyze the provincial characteristics of pig prices, and cluster analysis is used to verify it. This article enriches the research methods of African swine fever public opinion analysis, and for the first time the text processing method of public opinion to be applied to the public opinion analysis of swine fever, and provides reference opinions for domestic-related enterprises and governments on pig production regulation and pork pricing.

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