COVID-19对人类个性的影响:基于机器学习工具文档建模的分析

Amitabha Acharya, Aman Aryan, Sujay Saha, Anupam Ghosh
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引用次数: 1

摘要

2019年冠状病毒病(COVID-19)严重影响了全球。这一病毒的迅速传播和预防措施对全世界所有人的生活产生了全方位的影响。对病毒的焦虑以及社会限制对心理健康构成了挑战,并可能产生严重的心理后果。在这项研究中,我们的目的是分析COVID-19是否已经从社交媒体文本(如Twitter)中对全世界所有人的众所周知的五因素人格特征进行了任何重大改变。我们首先在基准论文数据集上训练和验证五个机器学习模型,然后在预处理的Twitter数据集上对这些模型进行测试,该数据集由pre_covid和post_covid tweets组成。这项研究的新颖之处在于,它分析并确立了这样一个事实,即在这么短的时间内,COVID-19无法在全世界范围内对人类的个性产生非常重大的改变。我们比较了五种机器学习模型的性能,我们发现一个模型提供的结果也被其他模型证明是正确的。计算机期刊版权归牛津大学出版社/美国所有,未经版权所有者明确书面许可,其内容不得复制或通过电子邮件发送到多个网站或发布到listserv。但是,用户可以打印、下载或通过电子邮件发送文章供个人使用。这可以删节。对副本的准确性不作任何保证。用户应参阅原始出版版本的材料的完整。(版权适用于所有人。)
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Impact of COVID-19 on the Human Personality: An Analysis Based on Document Modeling Using Machine Learning Tools
Coronavirus disease of 2019 (COVID-19) has affected the globe terribly. The rapid spread of this virus and the precautionary measures to prevent it have impacted the lives of all human beings around the world in all dimensions. The anxieties over the virus along with the social restrictions have challenged the mental health and might have acute psychological consequences. In this study, our aim is to analyze whether COVID-19 has done any significant changes to very well-known five-factor personality traits of all the humans all over the world from social media text, such as Twitter. We first train and validate five machine learning models on the benchmark essays dataset and then those models are tested on the preprocessed Twitter dataset, consisting of pre_covid and post_covid tweets. The novelty of this study is to analyze and establish the fact that in this short period of time, COVID-19 cannot make very significant changes in the human personality all over the world. We have compared the performances of five machine learning models and what we have found is that the result provided by one model is also justified by the other models. [ FROM AUTHOR] Copyright of Computer Journal is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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