通过对在线新闻的语义网络分析预测消费者信心
Andrea Fronzetti Colladon1, Francesca Grippa2, Barbara Guardabascio3
1Department of Engineering, University of Perugia, Via G. Duranti 93, 06125, Perugia, Italy. andrea.fronzetticolladon@unipg.it.
Scientific reports
|July 21, 2023
概括
在线新闻显著影响消费者对经济的看法. 分析了180万篇文章,发现关键词可以预测对经济状况和消费者信心的判断,提供了一种新的估计方法.
科学领域:
- 计算社会科学 计算社会科学
- 经济心理学 经济心理学
- 文本挖掘 (Text Mining) 是一个很好的方法.
背景情况:
- 传统的消费者信心调查有其局限性.
- 在线新闻是影响公众看法信息的不断增长的来源.
- 了解媒体内容与经济情绪之间的联系至关重要.
研究的目的:
- 调查在线新闻对消费者对经济和社会状况的看法的影响.
- 评估在线文章中的经济关键词对消费者信心的预测能力.
- 开发一种用于估计消费者信心的创新指标.
主要方法:
- 意义网络分析了超过180万篇意大利在线新闻文章 (4年期间).
- 文本挖掘技术用于识别和量化经济关键字的语义重要性.
- 关键词突出度和消费者信心指数 (CCI) 数据之间的相关性分析.
主要成果:
- 在经济关键词的语义重要性和消费者对家庭和国家经济状况的判断之间发现了强烈的预测关系.
- 开发的指标显示了消费者信心的显著预测能力.
- 该方法成功地使用文本挖掘和社交网络分析的组合分析了大型文本数据.
结论:
- 通过语义网络分析的在线新闻内容,可以有效地预测消费者经济观念的变化.
- 这一新型指标提供了一种补充传统调查的方法,用于估计消费者信心.
- 这些发现强调了大文本数据分析在经济和社会研究中的潜力.
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