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分析印度公众在新冠疫情期间对焦虑、压力和创伤的看法 - 对 84 万条推文的机器学习研究。

Analyzing Indian general public's perspective on anxiety, stress and trauma during Covid-19 - A machine learning study of 840,000 tweets.

机构信息

National Institute of Technology, Trichy, India.

National Institute of Technology, Trichy, India.

出版信息

Diabetes Metab Syndr. 2021 May-Jun;15(3):667-671. doi: 10.1016/j.dsx.2021.03.016. Epub 2021 Mar 24.

Abstract

BACKGROUND AND AIMS

Ever since COVID-19 was declared a pandemic by WHO in late March 2020, more and more people began to share their opinions online about the anxiety, stress, and trauma they suffered because of the pandemic. However, very few studies were conducted to analyze the general public's perception of what causes stress, anxiety, and trauma during COVID-19. This study focuses particularly on understanding Indian citizens.

METHODS

By using Machine learning techniques, particularly Natural language processing, this study focuses on understanding the attitude of Indian citizens while discussing the anxiety, stress, and trauma created because of COVID-19 and the major reasons that cause it. We used Tweets as data for this study. We have used 840,000 tweets for this study.

RESULTS

Our sentiment analysis study revealed the interesting fact that, even while discussing about the stress, anxiety, and trauma caused by COVID-19, most of the tweets were in neutral sentiments. Death and Lockdown caused by the COVID-19 were the two most important aspects that cause stress, anxiety, and Trauma among Indian citizens.

CONCLUSION

It is important for policymakers and health professionals to understand common citizen's perspectives of what causes them stress, anxiety, and trauma to formulate policies and treat the patients. Our study shows that Indian citizens use social media to share their opinions about COVID-19 and as a coping mechanism in unprecedented time.

摘要

背景与目的

自 2020 年 3 月世界卫生组织宣布 COVID-19 大流行以来,越来越多的人开始在网上分享他们因疫情而感到的焦虑、压力和创伤。然而,很少有研究分析公众对 COVID-19 期间压力、焦虑和创伤的普遍看法。本研究特别关注印度公民的看法。

方法

本研究使用机器学习技术,特别是自然语言处理,旨在了解印度公民在讨论 COVID-19 引起的焦虑、压力和创伤以及造成这些问题的主要原因时的态度。我们将推文用作本研究的数据。我们使用了 84 万条推文进行了这项研究。

结果

我们的情感分析研究揭示了一个有趣的事实,即在讨论 COVID-19 带来的压力、焦虑和创伤时,大多数推文的情绪是中立的。COVID-19 导致的死亡和封锁是印度公民感到压力、焦虑和创伤的两个最重要的方面。

结论

政策制定者和卫生专业人员了解普通公民对导致他们压力、焦虑和创伤的因素的看法非常重要,以便制定政策和治疗患者。我们的研究表明,印度公民在社交媒体上分享他们对 COVID-19 的看法,并将其作为在前所未有的时期的应对机制。

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