通过 Twitter 分析探索长新冠患者的情绪与心理健康
Exploring the Emotional and Mental Well-Being of Individuals with Long COVID Through Twitter Analysis
AI总结：
本研究通过对 Twitter 内容进行分类、六种基本情绪检测和话题提取，分析长新冠患者的情绪与心理健康，发现负面情绪长期主导并在关键时期出现高峰。
摘要：
COVID-19 疫情导致了长新冠（Long COVID）的出现，这是感染后持续存在的一组症状。长新冠患者还可能面临心理健康挑战，因此了解个体的情绪与心理健康至关重要。本研究旨在更深入地理解长新冠患者的情绪与心理健康，识别他们最关注的话题，并探讨其情绪与社交媒体活动之间的潜在关联。具体而言，我们根据内容将推文分为四类，检测六种基本情绪的存在，并提取主要话题。分析显示，在整个研究期间负面情绪占主导，并在新 COVID 变异株暴发等关键时期出现两次高峰。本研究结果对制定应对长新冠患者心理健康挑战的政策和措施具有启示意义，并为未来工作奠定基础。
英文摘要：
The COVID-19 pandemic has led to the emergence of Long COVID, a cluster of symptoms that persist after infection. Long COVID patients may also experience mental health challenges, making it essential to understand individuals' emotional and mental well-being. This study aims to gain a deeper understanding of Long COVID individuals' emotional and mental well-being, identify the topics that most concern them, and explore potential correlations between their emotions and social media activity. Specifically, we classify tweets into four categories based on the content, detect the presence of six basic emotions, and extract prevalent topics. Our analyses reveal that negative emotions dominated throughout the study period, with two peaks during critical periods, such as the outbreak of new COVID variants. The findings of this study have implications for policy and measures for addressing the mental health challenges of individuals with Long COVID and provide a foundation for future work.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
