Exploring the Impact of COVID-19 on Aviation Industry: A Text Mining Approach

Swapna Gottipati, Kyong Jin Shim, Angeline Weiling Jiang, Andre Justin Sheng Wei Lee
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引用次数: 3

Abstract

Our study presents a comprehensive analysis of news articles from FlightGlobal website during the first half of 2020. Our analyses reveal useful insights on themes and trends concerning the aviation industry during the COVID-19 period. We applied text mining and NLP techniques to analyse the articles for extracting the aviation themes and article sentiments (positive and negative). Our results show that there is a variation in the sentiment trends for themes aligned with the real-world developments of the pandemic. The article sentiment analysis can offer industry players a quick sense of the nature of developments in the industry. Our article theme analysis adds further value by summarizing the common key topics within the positive and negative corpora, allowing stakeholders in the aviation industry to gain more insights on areas of concerns or aspects that are affected by the pandemic.
探索COVID-19对航空业的影响:一种文本挖掘方法
我们的研究对2020年上半年FlightGlobal网站上的新闻文章进行了全面分析。我们的分析揭示了有关2019冠状病毒病期间航空业主题和趋势的有用见解。我们应用文本挖掘和自然语言处理技术对文章进行分析,以提取航空主题和文章情绪(积极和消极)。我们的研究结果表明,对与疫情现实发展相一致的主题的情绪趋势存在差异。文章情绪分析可以让行业参与者快速了解行业发展的本质。我们的文章主题分析通过总结积极和消极语料库中的共同关键主题,进一步增加了价值,使航空业的利益相关者能够更深入地了解受疫情影响的关注领域或方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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