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Unveiling the Journey: Analyzing Information Seeking Events in Online Recovery Discourse

SEPTEMBER 22, 2023

Sarah M. Preum, PhD
Assistant Professor
Department of Computer Science
Dartmouth College

About the Presentation: Medications for opioid use disorder (MOUD), such as methadone or buprenorphine, are proven life-saving treatments, yet individuals seeking or undergoing MOUD often encounter significant information gaps that affect their treatment journey. For instance, pregnant women may hesitate due to concerns about fetal development, and those with fentanyl dependency may seek effective strategies for buprenorphine induction to prevent withdrawal. In many cases, these individuals turn to social media instead of healthcare providers due to stigma, trust issues, and limited resources, making online platforms a valuable source of self-reported MOUD treatment information.

In this presentation, we’ll explore the methodology behind harnessing large-scale social media data to extract clinically relevant insights for MOUD treatment. We’ll delve into data collection, coding, and mixed-method data analysis processes, sharing intriguing findings from our analysis. Additionally, we’ll demonstrate the potential of state-of-the-art natural language processing methods, including generative AI like ChatGPT, in deciphering this data. Lastly, we’ll discuss the promising future of interdisciplinary research, spanning AI, data science, human-centered design, and public health, in advancing our understanding of MOUD treatment.

 About the Presenter: Dr. Sarah Preum is an Assistant Professor in Computer Science at Dartmouth, holding an adjunct professorship in Biomedical Data Science at the Geisel School of Medicine. Specializing in pioneering and pragmatic machine-learning techniques, her work propels advancements in computational health. Dr. Preum’s primary research interests encompass natural language processing, temporal modeling, and human-AI interaction, all geared toward furnishing personalized decision support for specific digital health applications.

She earned her Ph.D. in Computer Science from the University of Virginia and subsequently embarked on a postdoctoral research role at Carnegie Mellon University’s School of Computer Science. In 2020, Dr. Preum’s academic excellence and commitment to equity and inclusion were acknowledged when she was recognized as one of the Rising Stars in Electrical Engineering and Computer Science (EECS), an international cohort of distinguished female faculty members. Throughout her academic journey, Dr. Preum has garnered numerous accolades, including the UVA Graduate Commonwealth Fellowship, the Adobe Research Scholarship, the NSF Smart and Connected Health Student Award, and the UVA Big Data Fellowship.