Suppr超能文献

基于新冠肺炎疫情期间社交媒体信息预测美国石油市场。

Forecasting the U.S. oil markets based on social media information during the COVID-19 pandemic.

作者信息

Wu Binrong, Wang Lin, Wang Sirui, Zeng Yu-Rong

机构信息

School of Management, Huazhong University of Science and Technology, Wuhan, 430074, China.

School of Information Engineering, Hubei University of Economics, Wuhan, 430205, China.

出版信息

Energy (Oxf). 2021 Jul 1;226:120403. doi: 10.1016/j.energy.2021.120403. Epub 2021 Mar 18.

Abstract

Accurate oil market forecasting plays an important role in the theory and application of oil supply chain management for profit maximization and risk minimization. However, the coronavirus disease 2019 (COVID-19) has compelled governments worldwide to impose restrictions, consequently forcing the closure of most social and economic activities. The latter leads to the volatility of the oil markets and poses a huge challenge to oil market forecasting. Fortunately, the social media information can finely reflect oil market factors and exogenous factors, such as conflicts and political instability. Accordingly, this study collected vast online oil news and used convolutional neural network to extract relevant information automatically. Oil markets are divided into four categories: oil price, oil production, oil consumption, and oil inventory. A total of 16,794; 9,139; 8,314; and 8,548 news headlines were collected in four respective cases. Experimental results indicate that social media information contributes to the forecasting of oil price, oil production and oil consumption. The mean absolute percentage errors are respectively 0.0717, 0.0144 and 0.0168 for the oil price, production, and consumption prediction during the COVID-19 pandemic. Marketers must consider the impact of social media information on the oil or similar markets, especially during the COVID-19 outbreak.

摘要

准确的石油市场预测在石油供应链管理的理论与应用中起着重要作用,有助于实现利润最大化和风险最小化。然而,2019年冠状病毒病(COVID-19)迫使世界各国政府实施限制措施,导致大多数社会和经济活动被迫关闭。这导致了石油市场的波动,给石油市场预测带来了巨大挑战。幸运的是,社交媒体信息能够很好地反映石油市场因素和外部因素,如冲突和政治不稳定。因此,本研究收集了大量在线石油新闻,并使用卷积神经网络自动提取相关信息。石油市场分为四类:油价、石油产量、石油消费和石油库存。在这四类情况中,分别收集了16794条、9139条、8314条和8548条新闻标题。实验结果表明,社交媒体信息有助于预测油价、石油产量和石油消费。在COVID-19大流行期间,油价、产量和消费预测的平均绝对百分比误差分别为0.0717、0.0144和0.0168。营销人员必须考虑社交媒体信息对石油或类似市场的影响,尤其是在COVID-19爆发期间。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验