The COVID-19 pandemic has affected lives of people from different countries
for almost two years. The changes on lifestyles due to the pandemic may cause
psychosocial stressors for individuals, and have a potential to lead to mental
health problems. To provide high quality mental health supports, healthcare
organization need to identify the COVID-19 specific stressors, and notice the
trends of prevalence of those stressors. This study aims to apply natural
language processing (NLP) on social media data to identify the psychosocial
stressors during COVID-19 pandemic, and to analyze the trend on prevalence of
stressors at different stages of the pandemic. We obtained dataset of 9266
Reddit posts from subreddit \rCOVID19_support, from 14th Feb ,2020 to 19th July
2021. We used Latent Dirichlet Allocation (LDA) topic model and lexicon methods
to identify the topics that were mentioned on the subreddit. Our result
presented a dashboard to visualize the trend of prevalence of topics about
covid-19 related stressors being discussed on social media platform. The result
could provide insights about the prevalence of pandemic related stressors
during different stages of COVID-19. The NLP techniques leveraged in this study
could also be applied to analyze event specific stressors in the future.

该研究应用自然语言处理技术对社交媒体数据进行分析，以确定 COVID-19 大流行期间的心理社会压力源，并分析各阶段压力源的流行趋势。结果可用于提供洞察力，以便为个人提供高质量的心理健康支持。