In progress
Python Programming for Social Workers
A Hands-On Guide to Natural Language Processing and Large Language Models in Research and Practice
Nari Yoo. Routledge, forthcoming.
Social workers work extensively with text data, and interest in large language models (LLMs) has created demand for computational text analysis skills that most social work programs do not yet teach. This hands-on textbook teaches social work students, researchers, and practitioners to write Python code that applies natural language processing (NLP) and LLM methods in research and in the AI workflows that agencies are adopting.
Written for readers with no programming background, the book is organized around the division between pre-LLM and LLM methods, so that readers learn when a dictionary, a classical classifier, an encoder model, a small open-weight model run locally, or a commercial LLM fits a task. Each chapter is built on a Google Colab notebook with worked code and exercises on social work text. Privacy, data rights, and security are covered with professional ethics before any method is taught, with the NASW Code of Ethics as the primary reference alongside guidance from other countries, and each LLM chapter opens with the ethical questions its methods raise.
Designed for MSW and PhD courses, the book teaches enough Python for readers to direct coding agents such as Claude Code and Codex, check their output, and take responsibility for the result.
Contents
Companion materials
Open-access companion materials will accompany the book: a GitHub repository with the code and sample datasets (synthetic case notes and public policy documents), a Colab notebook for each chapter, and password-protected instructor resources (syllabi, coding assignments with solution notebooks, rubrics, and a test bank).