Mining the Impacts of COVID-19 Pandemic on the Labour Market

Joshua F. Smallwood, Chenru Zhao, C. Leung, Yan Wen, Haolin Zheng
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引用次数: 6

Abstract

Under the influence of the pandemic environment, many people may have lost their jobs or on the verge of being laid off, while there are many new job seekers. Hence, the status of new jobs under the pandemic and how various industries are affected by the pandemic—including predicting future work trends—have become the focus of attention. In this paper, we present a social informatics solution to mine the impacts of COVID-19 pandemic on the labour market. We make good use of data mining (especially, frequent pattern mining), statistical analysis, and prediction. Evaluation of real-life Canadian labour market data demonstrates the practicality of our tool. Although we illustrate our ideas with the Canadian labour market, our solution can be adaptable to mine labour markets in other geographical locations.
挖掘COVID-19大流行对劳动力市场的影响
在疫情大环境的影响下,许多人可能失去了工作或面临下岗,而新的求职者也很多。因此,疫情下新就业岗位的状况以及不同行业如何受到疫情的影响,包括预测未来的工作趋势,成为人们关注的焦点。在本文中,我们提出了一种社会信息学解决方案,以挖掘COVID-19大流行对劳动力市场的影响。我们很好地利用了数据挖掘(特别是频繁的模式挖掘)、统计分析和预测。对现实生活中的加拿大劳动力市场数据的评估表明了我们工具的实用性。虽然我们以加拿大劳动力市场说明我们的想法,但我们的解决办法可以适用于其他地理位置的矿山劳动力市场。
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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