Language shared online through social media or messaging reflects people's thoughts and emotions. Processing this data with Natural Language Processing (NLP) and machine learning can reveal mental health and psychological traits. For example, analyzing Facebook posts enables me to predict depression before it is clinically diagnosed and highlight particular symptoms. At the population level, billions of geo-tagged Tweets can be used to monitor health risk patterns, including depression and anxiety trends across communities. Beyond assessment, I'm using Large Language Models (LLMs) to improve mental health care, including training therapists and assisting with Cognitive Behavioral Therapy. These applications of NLP and Al may lead to earlier and more effective interventions and improved access for underserved populations.

Speaker: Johannes Eichstaedt, Ph.D. Assistant Professor, Psychology & Human-Centered Al, Stanford University