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HAI Weekly Seminar with Johannes Eichstaedt - Measuring Physical and Mental Health Using Social Media | Stanford HAI

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eventSeminar

HAI Weekly Seminar with Johannes Eichstaedt - Measuring Physical and Mental Health Using Social Media

Status
Past
Date
Friday, January 24, 2020 11:00 AM - 12:00 PM PST/PDT
Topics
Sciences (Social, Health, Biological, Physical)
Communications, Media

The content shared on social media is among the largest data sets on human behavior in history. I leverage this data to address questions in the psychological sciences. Specifically, I apply natural language processing and machine learning to characterize and measure psychological phenomena with a focus on mental and physical health.

 

For depression, I will show that machine learning models applied to Facebook status histories can predict future depression as documented in the medical records of a sample of patients. For heart disease, the leading cause of death, I demonstrate how prediction models derived from geo-tagged Tweets can estimate county mortality rates better than gold-standard epidemiological models, and at the same time give us insight into the sociocultural context of heart disease. I will also present preliminary findings on my emerging project to measure the subjective well-being of large populations. Across these studies, I argue that AI-based approaches to social media can augment clinical practice, guide prevention, and inform public policy.

Johannes Eichstaedt
Ram and Vijay Shriram HAI Faculty Fellow, Assistant Professor (Research) of Psychology
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