As social media platforms are increasingly adopted, the data the data people leave behind is shining new light into our understanding of phenomena, ranging from socio-economic-political events to the spread of infectious diseases. This chapter presents research conducted in the past decade that has harnessed social media data in the service of mental health and well-being. The discussion is organized along three thrusts: a first that highlights how social media data has been utilized to detect and predict risk to varied mental health concerns; a second thrust that focuses on translation paradigms that can enable to use of such social media based algorithms in the real-world; and the final thrust that brings to the fore the ethical considerations and challenges that engender the conduct of this research as well as its translation. The chapter concludes by noting open questions and problems in this emergent area, emphasizing the need for deeper interdisciplinary collaborations and participatory research design, incorporating and centering on human agency, and attention to societal inequities and harms that may result from or be exacerbated in this line of computational social science research.

翻译：随着社交媒体平台的日益普及，人们留下的数据为理解从社会经济政治事件到传染病传播等各种现象提供了新的视角。本章综述了过去十年中利用社交媒体数据促进心理健康与福祉的相关研究。讨论围绕三个主要方向展开：首先重点阐述如何利用社交媒体数据检测和预测各类心理健康问题的风险；其次聚焦于能够使此类基于社交媒体的算法在现实世界中应用的转化范式；最后深入探讨开展此类研究及其转化过程中引发的伦理考量与挑战。本章最后指出了这一新兴领域的开放性问题，强调需要更深层次的跨学科合作与参与式研究设计，重视并围绕人类能动性展开研究，同时关注这种计算社会科学研究可能引发或加剧的社会不平等与潜在危害。