Tracking the Impact of COVID-19 and Lockdown Policies on Public Mental Health Using Social Media: Infoveillance Study

Abstract

Background: The COVID-19 pandemic and its corresponding preventive and control measures have increased the mental burden on the public. Understanding and tracking changes in public mental status can facilitate optimizing public mental health intervention and control strategies. Objective: This study aimed to build a social media–based pipeline that tracks public mental changes and use it to understand public mental health status regarding the pandemic. Methods: This study used COVID-19–related tweets posted from February 2020 to April 2022. The tweets were downloaded using unique identifiers through the Twitter application programming interface. We created a lexicon of 4 mental health problems (depression, anxiety, insomnia, and addiction) to identify mental health–related tweets and developed a dictionary for identifying health care workers. We analyzed temporal and geographic distributions of public mental health status during the pandemic and further compared distributions among health care workers versus the general public, supplemented by topic modeling on their underlying foci. Finally, we used interrupted time series analysis to examine the statewide impact of a lockdown policy on public mental health in 12 states. Results: We extracted 4,213,005 tweets related to mental health and COVID-19 from 2,316,817 users. Of these tweets, 2,161,357 (51.3%) were related to “depression,” whereas 1,923,635 (45.66%), 225,205 (5.35%), and 150,006 (3.56%) were related to “anxiety,” “insomnia,” and “addiction,” respectively. Compared to the general public, health care workers had higher risks of all 4 types of problems (all P