The COVID-19 Pandemic and Mental Health Concerns on Twitter in the United States

Senqi Zhang, Li Sun, Daiwei Zhang, Pin Li, Yue Liu, A. Anand, Zidian Xie, Dongmei Li
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引用次数: 10

Abstract

Background: Mental health illness is a growing problem in recent years. During the COVID-19 pandemic, mental health concerns (such as fear and loneliness) have been actively discussed on social media. Objective: In this study, we aim to examine mental health discussions on Twitter during the COVID-19 pandemic in the United States and infer the demographic composition of Twitter users who had mental health concerns. Methods: COVID-19 related tweets from March 5th, 2020 to January 31st, 2021 were collected through Twitter streaming API using COVID-19 related keywords (e.g., "corona", "covid19", "covid"). By further filtering using mental health keywords (e.g., "depress", "failure", "hopeless"), we extracted mental health-related tweets from the US. Topic modeling using the Latent Dirichlet Allocation model was conducted to monitor users' discussions surrounding mental health concerns. Demographic inference using deep learning algorithms (including Face++ and Ethnicolr) was performed to infer the demographic composition of Twitter users who had mental health concerns during the COVID-19 pandemic. Results: We observed a positive correlation between mental health concerns on Twitter and the COVID-19 pandemic in the US. Topic modeling showed that "stay-at-home", "death poll" and "politics and policy" were the most popular topics in COVID-19 mental health tweets. Among Twitter users who had mental health concerns during the pandemic, Males, White, and 30-49 age group people were more likely to express mental health concerns. In addition, Twitter users from the east and west coast had more mental health concerns. Conclusions: The COVID-19 pandemic has a significant impact on mental health concerns on Twitter in the US. Certain groups of people (such as Males, White) were more likely to have mental health concerns during the COVID-19 pandemic.
新冠肺炎疫情与美国推特上的心理健康问题
背景:近年来,心理健康疾病是一个日益严重的问题。在新冠肺炎大流行期间,社交媒体上积极讨论了心理健康问题(如恐惧和孤独)。目的:在本研究中,我们旨在研究新冠肺炎在美国大流行期间推特上的心理健康讨论,并推断有心理健康问题的推特用户的人口构成。方法:通过推特流媒体API收集2020年3月5日至2021年1月31日新冠肺炎相关推文,使用新冠肺炎相关关键词(如“corona”、“covid19”、“新冠肺炎”)。通过使用心理健康关键词(例如,“压抑”、“失败”、“绝望”)进行进一步过滤,我们从美国提取了与心理健康相关的推文。使用潜在狄利克雷分配模型进行主题建模,以监测用户围绕心理健康问题的讨论。使用深度学习算法(包括Face++和Ethnicoll)进行人口统计推断,以推断新冠肺炎大流行期间有心理健康问题的推特用户的人口统计组成。结果:我们观察到推特上的心理健康问题与美国新冠肺炎大流行之间存在正相关。主题模型显示,“待在家里”、“死亡调查”和“政治和政策”是新冠肺炎心理健康推文中最受欢迎的主题。在疫情期间有心理健康问题的推特用户中,男性、白人和30-49岁年龄段的人更有可能表达心理健康问题。此外,来自东海岸和西海岸的推特用户有更多的心理健康问题。结论:新冠肺炎大流行对美国推特上的心理健康问题产生了重大影响。在新冠肺炎大流行期间,某些人群(如男性、白人)更有可能出现心理健康问题。
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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CiteScore
3.70
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