Bagroy Shrey, Kumaraguru Ponnurangam, De Choudhury Munmun
Precog, IIIT-Delhi,
College of Computing, Georgia Tech,
Proc SIGCHI Conf Hum Factor Comput Syst. 2017 May;2017:1634-1646. doi: 10.1145/3025453.3025909.
Psychological distress in the form of depression, anxiety and other mental health challenges among college students is a growing health concern. Dearth of accurate, continuous, and multi-campus data on mental well-being presents significant challenges to intervention and mitigation efforts in college campuses. We examine the potential of social media as a new "barometer" for quantifying the mental well-being of college populations. Utilizing student-contributed data in Reddit communities of over 100 universities, we first build and evaluate a transfer learning based classification approach that can detect mental health expressions with 97% accuracy. Thereafter, we propose a robust campus-specific Mental Well-being Index: MWI. We find that MWI is able to reveal meaningful temporal patterns of mental well-being in campuses, and to assess how their expressions relate to university attributes like size, academic prestige, and student demographics. We discuss the implications of our work for improving counselor efforts, and in the design of tools that can enable better assessment of the mental health climate of college campuses.
大学生中以抑郁、焦虑和其他心理健康挑战形式存在的心理困扰,正日益成为一个健康问题。缺乏关于心理健康的准确、连续且多校区的数据,给大学校园的干预和缓解工作带来了重大挑战。我们研究了社交媒体作为量化大学生心理健康新“晴雨表”的潜力。利用来自100多所大学的Reddit社区中由学生提供的数据,我们首先构建并评估了一种基于迁移学习的分类方法,该方法能够以97%的准确率检测心理健康表达。此后,我们提出了一个稳健的针对特定校园的心理健康指数:MWI。我们发现MWI能够揭示校园中心理健康有意义的时间模式,并评估其表达与大学属性(如规模、学术声誉和学生人口统计学特征)之间的关系。我们讨论了我们的工作对于改进辅导员工作以及设计能够更好评估大学校园心理健康氛围的工具的意义。