Analyzing the Functionality and Efficient Operability of the Youth During COVID 19

Megha Mishra, R. Thareja, Vidushi Singla
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Abstract

The ongoing pandemic has increased stress and problems for people of all age groups. There has been a drastic change in the life of people due to this pandemic because of which they are suffering from mental stress, financial problems, anxiety, etc. Different measures such as lockdown and social distancing were adopted by almost every country to control the pandemic. People have lost jobs, have got salary cuts, and are suffering from great financial losses due to these measures which are causing mental stress to the people. The youth is also facing much problems due to closing of educational institutions, sudden shift toward online mode of education, and nonavailability of jobs due to falling economy in COVID. Hence, we prepared a questionnaire about the problems faced by people. The questions were divided into three sections - education, health, and lifestyle. The questionnaire was filled by individuals in the age group of 17-30 years in India. Responses were collected and analyzed using statistical techniques and machine learning algorithms such as KNN, logistic regression, and SVM. To compare the situations of the people in India with that in the other parts of the globe, we extracted data from Twitter. The results were plotted graphically to get a better understanding of data and the result set. Accuracy was calculated, and a confusion matrix was drawn to validate our calculations and conclusions. © 2022 selection and editorial matter, Shivani Bali, Sugandha Aggarwal, Sunil Sharma;individual chapters, the contributors.
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分析COVID - 19期间青年的功能和有效可操作性
目前的大流行病给所有年龄组的人都增加了压力和问题。由于这次大流行,人们的生活发生了巨大变化,他们遭受精神压力、经济问题、焦虑等。几乎每个国家都采取了封锁和保持社交距离等不同措施来控制疫情。由于这些措施给人们带来了精神压力,人们失去了工作,减薪,并遭受了巨大的经济损失。由于教育机构的关闭、突然转向在线教育、因新冠疫情导致的经济衰退而无法找到工作,青年们也面临着很多问题。因此,我们准备了一份关于人们面临的问题的调查问卷。这些问题被分为三个部分——教育、健康和生活方式。问卷由印度17-30岁年龄组的个人填写。使用统计技术和机器学习算法(如KNN、逻辑回归和支持向量机)收集和分析响应。为了比较印度人和世界其他地方的人的情况,我们从Twitter上提取了数据。将结果绘制成图形,以便更好地理解数据和结果集。计算了精度,并绘制了混淆矩阵来验证我们的计算和结论。©2022选择和编辑事项,Shivani Bali, Sugandha Aggarwal, Sunil Sharma;各个章节,贡献者。
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