Git Repository for Transcript Text Mining Tool
Abstract
This article will provide a case study of new processes for creating subject tags across multiple oral history recordings. It outlines a workflow that empowers student workers to run, modify, and expand these tags during the copyediting process. The goal is to produce richer, more accurate tagging, allowing future researchers to more easily identify connections across audio collections. The paper provides a detailed description of the workflow, explores the challenges it addresses, shares pedagogical experiences of transcribers, and examines the limitations of data-driven, human-edited automated tagging.
Content: CC BY-NC-ND 4.0 Andrew Weymouth 2024 (get source code).
Theme: Variation on workshop-template-b by evanwill
