使用机器学习分析COVID-19期间的人类倾向

Charu Gupta, D. Gaur, Prateek Agrawal, Deepali Virmani
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引用次数: 0

摘要

冠状病毒极大地影响了人类生活的各个方面,包括人类的心理和性格。在本文中,我们试图分析COVID-19大流行对人类健康的影响。我们提出了使用机器学习(HuDA_COVID)进行COVID-19期间的人类倾向分析,其中研究了年龄,就业,成瘾,压力水平等因素以进行人类倾向分析。对不同年龄段、地区和职业的个人进行了大规模调查,方法的准确度在87.5%到98%之间。研究表明,人们担心禁闭、工作和人际关系。此外,23%的受访者没有任何效果。45%和32%的人分别产生了积极和消极的影响。提出了一种新的健康状态加权赋值方法,这是COVID-19人的性格分析中的一项新研究。HuDA_COVID清楚地表明,需要对人类心理需求采取有条理的方法,以帮助社会组织为受影响的个人制定整体干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HuDA_COVID Human Disposition Analysis During COVID-19 Using Machine Learning
Coronavirus has greatly impacted various aspects of human life, including human psychology & human disposition. In this paper, we attempted to analyze the impact of the COVID-19 pandemic on human health. We propose Human Disposition Analysis during COVID-19 using machine learning (HuDA_COVID), where factors such as age, employment, addiction, stress level are studied for human disposition analysis. A mass survey is conducted on individuals of various age groups, regions & professions, and the methodology achieved varied accuracy ranges of 87.5% to 98%. The study shows people are worried about lockdown, work & relationships. Furthermore, 23% of the respondents have not had any effect. 45% and 32% have had positive and negative effects, respectively. It is a novel study in human disposition analysis in COVID-19 where a novel weighted assignment indicating the health status is also proposed. HuDA_COVID clearly indicates a need for a methodical approach towards the human psychological needs to help the social organizations formulating holistic interventions for affected individuals.
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