Inductive Analysis of Texts with Embeddings

Prof. Dustin Stoltz, Lehigh University

Word or text embeddings are a central component in modern language models, including those powering generative AI. Embeddings represent word meanings as positions in space, where words that are closer together are used in similar contexts or evoke similar concepts -- even if those words never actually co-occur. We navigate the meaning space created by embeddings directly using basic arithmetic, and in doing so, explore how meaning changes overtime or how meaning differs between different collections of texts. 

Dustin Stoltz is an Assistant Professor of Sociology and Cognitive Science at Lehigh University.  He studies a variety of topics in cultural and economic sociology and specializes in computational methods.  Five copies of his recently published book, Mapping Texts: Computational Text Analysis for the Social Sciences (coauthored with Marshall Taylor), will be raffled off to workshop registrants.  

Register here.

Lunch will be provided for registered attendees.

Hosted by the Center for Social Science Scholarship and cosponsored by the Departments of English; Sociology, Anthropology, & Public Health; Modern Languages, Linguistics, & Intercultural Communication; the Division of Information Technology; the Center for Scalable Data and Computational Science; and CGC-SCIPE.