In this work, we explore the relationship between depression and manifestations of happiness in social media. While the majority of works surrounding depression focus on symptoms, psychological research shows that there is a strong link between seeking happiness and being diagnosed with depression. We make use of Positive-Unlabeled learning paradigm to automatically extract happy moments from social media posts of both controls and users diagnosed with depression, and qualitatively analyze them with linguistic tools such as LIWC and keyness information. We show that the life of depressed individuals is not always bleak, with positive events related to friends and family being more noteworthy to their lives compared to the more mundane happy events reported by control users.
翻译：在这项工作中,我们探索抑郁症与社交媒体中幸福表现之间的关系。尽管围绕抑郁症的大部分工作都侧重于症状,但心理研究显示,追求幸福与被诊断为抑郁症之间有着紧密的联系。 我们利用积极、无标签的学习模式自动从社交媒体文章中提取控制者和被诊断为抑郁症使用者的快乐时刻,并用LIWC和关键信息等语言工具进行定性分析。 我们显示,抑郁症患者的生活并不总是暗淡,与朋友和家人有关的积极事件与其生活相比,与控制用户报告的更普通的快乐事件相比,更值得注意。
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