论文标题
使用主题建模探索COVID-19相关压力源
Exploring COVID-19 Related Stressors Using Topic Modeling
论文作者
论文摘要
COVID-19-大流行已经影响了来自不同国家的人们的生活近两年。由于大流行而导致的生活方式的变化可能会引起个人的心理压力，并有可能导致心理健康问题。为了提供高质量的心理健康支持，医疗保健组织需要确定COVID-19的特定压力源，并注意这些压力源流行的趋势。这项研究旨在将自然语言处理（NLP）应用于社交媒体数据上，以确定Covid-19大流行期间的社会心理压力源，并分析大流行不同阶段压力源流行的趋势。我们从2020年2月14日至2021年7月19日获得了Subreddit \ rcovid19_support的9266 REDDIT帖子的数据集。我们使用了潜在的Dirichlet分配（LDA）主题模型和Lexicon方法来识别SubreDdit上提到的主题。我们的结果提出了一个仪表板，以可视化有关在社交媒体平台上讨论的有关Covid-19相关压力源的主题流行趋势的趋势。结果可能会提供有关在Covid-19的不同阶段中大流行相关压力源流行率的见解。本研究中利用的NLP技术也可以应用于将来分析事件特定压力源。
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.
