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

Senqi Zhang,Li Sun,Yue Liu,Zidian Xie,Pin Li,Ajay Anand,Daiwei Zhang,Dongmei Li

doi:10.34133/2022/9758408

Senqi Zhang, Li Sun + Show 6 more

Open Access

https://doi.org/10.34133/2022/9758408

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Abstract

During the COVID-19 pandemic, mental health concerns (such as fear and loneliness) have been actively discussed on social media. We aim to examine mental health discussions on Twitter during the COVID-19 pandemic in the US and infer the demographic composition of Twitter users who had mental health concerns. COVID-19-related tweets from March 5th, 2020, to January 31st, 2021, were collected through Twitter streaming API using keywords (i.e., "corona," "covid19," and "covid"). By further filtering using keywords (i.e., "depress," "failure," and "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. Deep learning algorithms were performed to infer the demographic composition of Twitter users who had mental health concerns during the pandemic. 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. The COVID-19 pandemic has a significant impact on mental health concerns on Twitter in the US. Certain groups of people (such as Males and White) were more likely to have mental health concerns during the COVID-19 pandemic.

Highlights

Coronavirus disease 2019, known as COVID-19, was first reported to be detected in China in December 2019
To understand how the COVID-19 pandemic might affect mental health in the United States over time, we performed a temporal analysis on the number of tweets mentioning mental health in the US
Time series analysis showed that the correlation between the number of mental health tweets and the number of COVID-19 cases is 0.1196 with P value = 0.0005, which indicates that there is a mild positive correlation between the number of mental health-related tweets and the number of COVID-19 cases

Summary

Introduction

Coronavirus disease 2019, known as COVID-19, was first reported to be detected in China in December 2019. By July 5th, 2021, there were 30 million confirmed COVID-19 cases and 0.6 million related deaths in the US [1] During this COVID-19 pandemic, the US people endured living in isolation and communicating in distance, and the country suffered from huge economic losses. We aim to examine mental health discussions on Twitter during the COVID-19 pandemic in the US and infer the demographic composition of Twitter users who had mental health concerns. Deep learning algorithms were performed to infer the demographic composition of Twitter users who had mental health concerns during the pandemic. 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. Certain groups of people (such as Males and White) were more likely to have mental health concerns during the COVID-19 pandemic

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