Libby Hemphill is an Associate Professor and Research Associate Professor at the University of Michigan who blends computational methods and machine learning with deep expertise in digital curation to make social media archives more usable and impactful for researchers. She directs the Resource Center for Minority Data and the Social Media Archive at ICPSR, where her work quantifies how curation choices shape access, reuse, and the design of archival services. Her research also tackles online harm mitigation and the wellbeing of volunteer moderators by turning social media data into actionable moderation strategies. With 16 years in academia and a PhD in Information, she uniquely pairs HCI-informed scholarship with practical archive-building that influences national data stewardship practices. An oft-overlooked strength is her dual focus on both the technical architecture of archives and the sociotechnical consequences of curation decisions.
16 years of coding experience
16 years of employment as a software developer
Ph.D., Information, Ph.D., Information at University of Michigan - School of Information
Drake University
A.B., with honors, General Studies in the Humanities, A.B., with honors, General Studies in the Humanities at University of Chicago
Code for models described in Hemphill, L., & Schöpke-Gonzalez, A. M. (2020). Two Computational Models for Analyzing Political Attention in Social Media. Proceedings of the AAAI Conference on Web and Social Media, 14(1), 260–271. https://www.aaai.org/ojs/index.php/ICWSM/article/view/7297
Contributions:1 release, 27 commits, 4 PRs in 4 years 4 months
csvapipythontimespython-tools
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