新冠肺炎疫情阶段特征、公众情绪与农产品价格——基于微博文本挖掘的实证研究

doi:10.16036/j.issn.1000-2650.2021.05.018

摘要/Abstract

摘要： 【目的】新冠肺炎疫情期间,由于封城、交通管制等举措的实施,公众情绪变化剧烈,农产品价格波动明显,因此研究二者之间是否存在关联是一个有趣的议题。【方法】通过微博文本挖掘,分析疫情发展各个阶段公众讨论的主题,并通过情感分析量化公众情绪,进一步构建VAR格兰杰因果关系检验模型研究公众情绪变化与农产品价格波动的关系。【结果】潜伏期和爆发期对新冠病毒有关知识和防控措施的普及较为到位,但在蔓延期仍有谣言不断出现造成恐慌,干扰判断;公众情绪变化不仅是引起猪肉和蔬菜价格变化的格兰杰原因,也是引起牛肉、羊肉和水果价格变化的格兰杰原因;相对于整体情感值,负向情绪数量对农产品价格变化的解释效果更好;对于疫情严重地区,猪肉、牛肉的价格变动领先于公众情绪的变化。【结论】研究结果证实了公众情绪与农产品价格的关联性,为通过引导网络舆情形成健康良好的公众情绪,从而稳定公共卫生事件期间的农产品价格提供了理论参考。

关键词: 新冠肺炎疫情, 农产品价格, 文本挖掘, 情感分析

Abstract: 【Objective】 Due to the closure of the city, traffic control and other measures during the COVID-19 epidemic, the public mood changed dramatically and agricultural prices fluctuated significantly. Therefore, it is an interesting topic to study whether there is a correlation between them.【Method】 Weibo text mining was used to analyze the topics the public discussed at each stage of the epidemic development, and quantified the public sentiment through sentiment analysis to further construct the VAR granger causality test model to study the relationship between public sentiment and agricultural product price fluctuations.【Result】 The knowledge and prevention and control measures of COVID-19 were well popularized in the incubation and outbreak period, but there were still rumors in the spread period, causing panic and interfering with judgment; the change in public sentiment is not only the granger cause of the change in pork and vegetable prices, but also the granger cause of the change in beef, mutton and fruit prices; compared with the overall emotional value, the negative emotional quantity has a better explanation for the change of agricultural product price; for the hardest-hit areas, price changes in pork and beef have outpaced changes in public sentiment. 【Conclusion】 The research results confirmed the correlation between public sentiment and agricultural product prices, providing a theoretical reference for the formation of healthy public sentiment through guiding online public opinion, so as to stabilize agricultural product prices during public health events.

Key words: COVID-19, agricultural product price, text mining, sentiment analysis

中图分类号:

C912.63

邵小彧, 李冬梅, 刘云强. 新冠肺炎疫情阶段特征、公众情绪与农产品价格——基于微博文本挖掘的实证研究[J]. 四川农业大学学报, 2021, 39(5): 688-696.

SHAO Xiaoyu, LI Dongmei, LIU Yunqiang. Characteristics of the COVID-19 Epidemic Stage, Public Sentiment, and Agricultural Product Price: An Empirical Study Based on the Weibo Text Mining[J]. Journal of Sichuan Agricultural University, 2021, 39(5): 688-696.

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