通过情绪分析来管理意外事件期间的需求波动:COVID-19大流行病的案例研究
Angie Nguyen1, Samir Lamouri1, Robert Pellerin2
1LAMIH CNRS, Arts et Métiers Paris Tech, Paris, France.
概括
新闻媒体的情绪强烈地预测了危机期间的消费需求波动. 这一发现为改善流行病等意外情况的需求预测提供了宝贵的见解.
科学领域:
- 供应链管理 供应链管理
- 消费者行为分析 消费者行为分析
- 数据科学数据科学数据科学
背景情况:
- 像流行病这样的意外事件会导致供应链中断和市场波动.
- 现有的人工智能 (AI) 和数据分析模型在危机期间与需求波动作斗争.
- 随着COVID-19的流行,当前需求预测系统的局限性得到了凸显.
研究的目的:
- 调查新闻媒体情绪对消费者行为的影响.
- 评估媒体情绪在意想不到的事件期间对需求预测的预测能力.
主要方法:
- 数据收集和分析准备.
- 情绪分析模型的开发.
- 在COVID-19期间,对新闻情绪和药物消费之间的相关性的统计分析.
主要成果:
- 在新闻媒体情绪和消费变化之间发现了显著的正相关性.
- 媒体情绪显示出强大的需求预测预测能力.
结论:
- 新闻媒体的情绪是影响危机期间消费者购买行为的关键因素.
- 纳入媒体情绪分析可以增强对计划外事件的需求预测模型.
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