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Blending Social Media and Machine Learning to Improve Mental Health: Harnessing the Potentials and Avoiding the Pitfalls

Talk by Munmun De Choudhury, Georgia Tech

Abstract

Social media data is being increasingly used to computationally learn about and infer the mental health states of individuals and populations. Despite being touted as a powerful means to shape interventions and impact mental health recovery, little do we understand about the theoretical, domain, and psychometric validity of this novel information source, or its underlying biases, when appropriated to augment conventionally gathered data, such as clinical assessments and verbal self-reports. This talk presents a critical analytic perspective on the pitfalls of social media signals of mental health, especially when they are derived from “proxy” diagnostic indicators, often removed from the real-world context in which they are likely to be used. Then, to overcome these pitfalls, this talk presents results from two case studies, where computational algorithms to glean mental health insights from social media were developed in a context-centered way, in collaboration with domain experts and stakeholders. The first of these case studies, a collaboration with Northwell Health, focuses on the individual-perspective, and reveals the ability and implications of using social media data of consented schizophrenia patients to forecast relapse and support clinical decision-making. Scaling up to populations, in collaboration with the Centers for Disease Control and Prevention and towards influencing public health policy, the second case study seeks to forecast nationwide rates of suicide fatalities using social media signals, in conjunction with health services data. The talk concludes with discussions of the path forward, emphasizing the need for a collaborative, multi-disciplinary research agenda, that incorporates methodological rigor, ethics, and accountability.

Biography

Munmun De Choudhury is an assistant professor of Interactive Computing at Georgia Tech where she directs the Social Dynamics and Wellbeing Lab. Dr. De Choudhury is best known for laying the foundation of a new line of research focusing on assessing and improving personal and societal mental health from online social interactions. In her relatively short academic career, Dr. De Choudhury has been recognized with the Complex Systems Society – Junior Scientific Award in 2019, the James D. Lester III Family Award in 2018, the James Edenfield Faculty Fellowship in 2015, multiple best paper and honorable mention awards from the ACM and AAAI, and extensive coverage in popular press like the New York Times, the NPR, and the BBC. Earlier, Dr. De Choudhury was a faculty associate with the Berkman Klein Center for Internet and Society at Harvard, a postdoc at Microsoft Research, and obtained her PhD in Computer Science from Arizona State University.

Information

  • At 16:15 room BC 420 (see map)
From: 16 Dec, 2019
To: 16 Dec, 2019

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