JMIR Publications

ABSTRACT

Background:

The burden of mental health during COVID-19 disproportionately affects communities who are already at high-risk. In particular, long-lasting social distancing measures raise serious concerns for already socially marginalized communities or at high-risk of mental disorders, including senior citizens who live alone, people with disabilities, and low-income families. Given the media's daily role and exposures in meaning-making, media analysis is a useful approach to understanding patterns in reporting trends and popular topics in public discourse.

Objective:

The goal of the study is to investigate reporting trends and identify topics in the news about depression among vulnerable populations in South Korea, shortly before and during COVID-19 through the latent Dirichlet allocation (LDA) topic modeling method.

Methods:

We used the BigKinds database to collect Korean news articles related to mental health and marginalized communities between January 20, 2019, and January 20, 2021, in Korea. We used R software and packages (“tm”, “textmineR”, “topicmodels”, “LDAvis”) to process and analyze the data. We applied the LDA topic modeling method on news keywords to generate corresponding topic names and popular terms. We then visualized the models through multidimensional scaling to identify overlapping topics and group them under common themes.

Results:

After removing duplicates and irrelevant articles, we identified 412 news reports between January 20, 2019, to January 20, 2021. We used coherence values to choose the optimal number of topics for each year. Results showed that the number of articles related to depression and vulnerable populations increased by three-folds during the COVID-19 pandemic (n=306) between January 21, 2020, and January 20, 2021, compared to articles from 2019 (n=106). For articles from 2019, we chose 18 topics and divided them into 12 common themes. For articles from 2020, we chose 12 topics and divided them into seven themes. In 2020, new top themes emerged, including ‘Theme 1: social welfare programs (therapy support, mask donations, visiting programs) for marginalized communities” (N= 114, 37.25%), “Theme 2: social welfare programs for senior citizens and suicide prevention programs” (N= 72, 23.53%), and “Theme 3: mental health during COVID-19” (N=60, 19.61%).

Conclusions:

South Korea, news articles related to depression and its marginalized society increased significantly after the COVID-19 pandemic. The South Korean society became primarily concerned with suicide prevention programs, mental health during COVID-19, and social welfare programs for vulnerable communities, such as mask donations, home-visiting programs, and support groups. It is critical for policymakers and public health officials to understand what common topics on social issues, such as mental health concerns during COVID-19, are being discussed in the news to better serve communities in welfare blind-spots. Future studies can examine the relationship between news media and its effect on policy development, as well as critical discourse analysis and sentiment analysis of news articles.