Depression and Self-Harm Risk Assessment in Online Forums

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 2968–2978 Copenhagen, Denmark, September 7–11, 2017. c⃝2017 Association for Computational Linguistics Depression and Self-Harm Risk Assessment in Online Forums Andrew Yates†∗ Arman Cohan‡∗ Nazli Goharian‡ †Max Planck Institute for Informatics, Saarland Informatics Campus Saarbruecken, Germany ‡Information Retrieval Lab, Department of Computer Science, Georgetown University, Washington DC, USA ayates@mpi-inf.mpg.de {arman,nazli}@ir.cs.georgetown.edu Abstract Users suffering from mental health con- ditions often turn to online resources for support, including specialized online sup- port communities or general communities such as Twitter and Reddit. In this work, we present a framework for supporting and studying users in both types of communi- ties. We propose methods for identifying posts in support communities that may in- dicate a risk of self-harm, and demonstrate that our approach outperforms strong pre- viously proposed methods for identifying such posts. Self-harm is closely related to depression, which makes identifying de- pressed users on general forums a cru- cial related task. We introduce a large- scale general forum dataset consisting of users with self-reported depression diag- noses matched with control users. We show how our method can be applied to effectively identify depressed users from their use of language alone. We demon- strate that our method outperforms strong baselines on this general forum dataset. 1 Introduction Mental health remains a major challenge in pub- lic health care. Depression is one of the most common mental disorders and 350 million peo- ple are estimated to suffer from depression world- wide (WHO, 2010). In 2014 an estimated 7% of all U.S. adults had experienced at least one ma- jor depressive disorder (2015). Suicide and self- harm are major related concerns in public men- tal health. Suicide is one of the leading causes of death (CDC, 2015), and each suicide case has major consequences on the physical and emotional ∗ The first two authors contributed equally to this work. well-being of families and on societies in general. Therefore identifying individuals at risk of self- harm and providing support to prevent it remains an important problem (Ferrari et al., 2014). Social media is often used by people with men- tal health problems to express their mental is- sues and seek support. This makes social media a significant resource for studying language re- lated to depression, suicide, and self-harm, as well as understanding the authors’ reasons for mak- ing such posts, and identifying individuals at risk of harm (Coppersmith et al., 2014a). Depression and suicide are closely related given that depres- sion is the psychiatric diagnosis most commonly associated with suicide. Research has demon- strated that forums are powerful platforms for self- disclosure and social support seeking around men- tal health concerns (De Choudhury and De, 2014; Manikonda and De Choudhury, 2017). Such sup- port forums are often staffed by moderators who are mental health experts, trained volunteers, or more experienced users whose role is to identify forum posts suggesting that a user is at risk of self- harm and to provide support. Studies have …

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