Studies on intergenerational relationships between parents and children in Asian American families highlight their impact on mental health and well-being. This study investigates the role of ambivalent emotions in online narratives shared by Asian and Asian American children on the subreddit, r/Asianparentstories. By employing a BERT-based model to detect emotion at the sentence level and depressive symptoms at the post level, we analyze mixed feelings to better understand how they predict depressive symptoms. First, among 28 detectable, eight (realization, approval, sadness, anger, curiosity, annoyance, disappointment, disapproval) comprise over 50%, exhibiting significant co-occurrence among themselves and with other emotions. Second, we find the co-occurrence of multiple emotions, indicating that emotions in a single post are not limited to consistently positive or negative feelings. Finally, our findings indicate that while negative emotion pairs (e.g., confusion-grief, anger-grief) are associated with depressive symptoms, positive emotion pairs (e.g., admiration-realization, amusement-joy) negatively correlate with depressive symptoms, and combinations of ambivalent emotions indicate varied results in predicting depressive symptoms. These findings highlight the importance of automated emotion classification and the need to consider emotional ambivalence, which holds practical and clinical implications for understanding the dynamics of parent-child relationships.

翻译：针对亚裔美国家庭中父母与子女代际关系的研究，凸显了其对心理健康与福祉的影响。本研究通过分析亚裔及亚裔美国子女在Reddit论坛子版块r/Asianparentstories发布的在线叙事，探讨矛盾情感在其中扮演的角色。我们采用基于BERT的模型在句子层面检测情感，在帖子层面检测抑郁症状，通过分析混合情感以深入理解其如何预测抑郁症状。首先，在28种可检测情感中，有八种情感（领悟、赞同、悲伤、愤怒、好奇、恼怒、失望、反对）占比超过50%，且这些情感彼此之间以及与其他情感存在显著共现关系。其次，我们发现多种情感常同时出现，表明单个帖子中的情感并不局限于持续积极或消极的情绪状态。最后，研究结果显示：消极情感配对（如困惑-悲痛、愤怒-悲痛）与抑郁症状呈正相关，积极情感配对（如钦佩-领悟、愉悦-欣喜）则与抑郁症状呈负相关，而矛盾情感组合在预测抑郁症状时呈现差异化结果。这些发现凸显了自动化情感分类的重要性，并指出需关注情感矛盾性，这对理解亲子关系动态具有实践与临床意义。