Lu Guang, Businger Martin, Dollfus Christian, Wozniak Thomas, Fleck Matthes, Heroth Timo, Lock Irina, Lipenkova Janna
Institute of Communication and Marketing, Lucerne University of Applied Sciences and Arts, Zentralstrasse 9, Lucerne, 6002 Switzerland.
Institute of Language Competence, ZHAW Zurich University of Applied Sciences, Theaterstrasse 17, Winterthur, 8401 Switzerland.
Int J Data Sci Anal. 2023;15(3):291-312. doi: 10.1007/s41060-022-00364-7. Epub 2022 Oct 6.
Over the past two years, organizations and businesses have been forced to constantly adapt and develop effective responses to the challenges of the COVID-19 pandemic. The acuteness, global scale and intense dynamism of the situation make online news and information even more important for making informed management and policy decisions. This paper focuses on the economic impact of the COVID-19 pandemic, using natural language processing (NLP) techniques to examine the news media as the main source of information and agenda-setters of public discourse over an eight-month period. The aim of this study is to understand which economic topics news media focused on alongside the dominant health coverage, which topics did not surface, and how these topics influenced each other and evolved over time and space. To this end, we used an extensive open-source dataset of over 350,000 media articles on non-medical aspects of COVID-19 retrieved from over 60 top-tier business blogs and news sites. We referred to the World Economic Forum's Strategic Intelligence taxonomy to categorize the articles into a variety of topics. In doing so, we found that in the early days of COVID-19, the news media focused predominantly on reporting new cases, which tended to overshadow other topics, such as the economic impact of the virus. Different independent news sources reported on the same topics, showing a herd behavior of the news media during this global health crisis. However, a temporal analysis of news distribution in relation to its geographic focus showed that the rise in COVID-19 cases was associated with an increase in media coverage of relevant socio-economic topics. This research helps prepare for the prevention of social and economic crises when decision-makers closely monitor news coverage of viruses and related topics in other parts of the world. Thus, monitoring the news landscape on a global scale can support decision-making in social and economic crises. Our analyses point to ways in which this monitoring and issues management can be improved to remain alert to social dynamics and market changes.
在过去两年里，各组织和企业被迫不断适应并制定有效的应对措施，以应对新冠疫情带来的挑战。形势的严峻性、全球范围以及高度动态性使得在线新闻和信息对于做出明智的管理和政策决策变得更加重要。本文聚焦于新冠疫情的经济影响，运用自然语言处理（NLP）技术，在八个月的时间里，将新闻媒体作为信息的主要来源以及公共话语的议程设置者进行研究。本研究的目的是了解新闻媒体在主要的健康报道之外关注了哪些经济话题，哪些话题没有出现，以及这些话题如何相互影响并随时间和空间演变。为此，我们使用了一个广泛的开源数据集，该数据集包含从60多个顶级商业博客和新闻网站检索到的35万多篇关于新冠疫情非医疗方面的媒体文章。我们参考世界经济论坛的战略情报分类法，将这些文章归类为各种主题。通过这样做，我们发现，在新冠疫情初期，新闻媒体主要集中报道新病例，这往往使其他话题，如病毒的经济影响，黯然失色。不同的独立新闻来源报道相同的话题，显示出在这场全球健康危机中新闻媒体的从众行为。然而，对新闻分布与其地理关注点的时间分析表明，新冠病例的增加与媒体对相关社会经济话题的报道增加有关。这项研究有助于在决策者密切关注世界其他地区病毒及相关话题的新闻报道时，为预防社会和经济危机做好准备。因此，在全球范围内监测新闻格局可以支持社会和经济危机中的决策。我们的分析指出了可以改进这种监测和问题管理的方法，以便对社会动态和市场变化保持警惕。
