The COVID-19 pandemic has disproportionately impacted the lives of minorities, such as members of the LGBTQ community (lesbian, gay, bisexual, transgender, and queer) due to pre-existing social disadvantages and health disparities. Although extensive research has been carried out on the impact of the COVID-19 pandemic on different aspects of the general population's lives, few studies are focused on the LGBTQ population. In this paper, we develop and evaluate two sets of machine learning classifiers using a pre-pandemic and a during-pandemic dataset to identify Twitter posts exhibiting minority stress, which is a unique pressure faced by the members of the LGBTQ population due to their sexual and gender identities. We demonstrate that our best pre- and during-pandemic models show strong and stable performance for detecting posts that contain minority stress. We investigate the linguistic differences in minority stress posts across pre- and during-pandemic periods. We find that anger words are strongly associated with minority stress during the COVID-19 pandemic. We explore the impact of the pandemic on the emotional states of the LGBTQ population by adopting propensity score-based matching to perform a causal analysis. The results show that the LGBTQ population have a greater increase in the usage of cognitive words and worsened observable attribute in the usage of positive emotion words than the group of the general population with similar pre-pandemic behavioral attributes. Our findings have implications for the public health domain and policy-makers to provide adequate support, especially with respect to mental health, to the LGBTQ population during future crises.

翻译：COVID-19疫情由于既存的社会劣势和健康差距，对少数群体（如LGBTQ社群成员：女同性恋、男同性恋、双性恋、跨性别者和酷儿）的生活产生了不成比例的影响。尽管已有大量研究探讨了COVID-19疫情对普通人群生活各个层面的影响，但针对LGBTQ群体的研究却寥寥无几。本文利用疫情前和疫情期间的两个数据集，开发并评估了两组机器学习分类器，用于识别展示少数群体压力的推特帖子——这种压力是LGBTQ群体成员因其性取向和性别认同而面临的独特压力。我们证明，无论是疫情前还是疫情期间的最优模型，在检测包含少数群体压力的帖子时均表现出强劲且稳定的性能。我们探究了疫情前后时期少数群体压力帖子中的语言差异，发现愤怒词汇在COVID-19疫情期间与少数群体压力显著相关。通过采用基于倾向得分的匹配进行因果分析，我们考察了疫情对LGBTQ群体情绪状态的影响。结果表明，与具有相似疫情前行为特征的普通人群相比，LGBTQ群体在认知词汇使用上增长更大，同时在积极情绪词汇的使用上可观测属性恶化。我们的研究结果为公共卫生领域和政策制定者提供了启示，以便在未来危机中为LGBTQ群体提供充分支持，尤其是在心理健康方面。