Text and Data Mining Literacy for Librarians

Whitney Kramer (Edited by), Iliana Burgos (Edited by), Evan Muzzall (Edited by)

9798892555951

Paperback / softback, published 27 October 2025

434 pages
25.4 x 17.8 x 2.5 cm, 0.794 kg

Text and data mining (TDM) is the process of using automated techniques to derive information from large sets of digital content. Librarians who liaise with a wide range of academic disciplines need TDM skills to support research at their institutions.

Text and Data Mining Literacy for Librarians collects ways that academic libraries are supporting TDM literacy through services, workflows, and professional development. In five parts, it offers a variety of perspectives, insights, and experiences that can help you address the challenges of supporting TDM research, fit it into your existing reference and instruction work, and conduct your own.

• Essentials of Text and Data Mining (TDM) Literacy
• Data Literacy, Licensing, and Management Challenges with TDM
• TDM Research in Action: Practical Applications and Case Studies
• Generating Insights from Library Reference Data
• Proprietary TDM Software: Examples and Implementations

Introduction
Whitney Kramer, Iliana Burgos, and Evan Muzzall

Part I: Essentials of Text and Data Mining (TDM) Literacy
Chapter 1. Language, Variation, and Change
Heather Froehlich

Chapter 2. Reference Interview Recommendations for Text and Data Mining
Laura Egan

Chapter 3. You Are Here: Mapping TDM Consults Across Disciplines and Infrastructures
Jessica C. Hagman and Mary Borgo Ton

Chapter 4. Navigating Text Data Mining Training for Humanities Librarians: A Microcredential Case Study from Baylor University
Ellen Hampton Filgo, Laura Semrau, and Ezra Choe
Chapter 5. Exploring the Power of Text Data Mining: Syllabi Analysis for Information Literacy Instructional Outreach
Amy James and Joshua Been

Chapter 6. Mining Expertise to Maximize Support: Leveraging Campus Partnerships for Text and Data Mining
Cody Hennesy and Michael Beckstrand

Chapter 7. Envisioning Librarians’
New Roles in the Age of Text and Data Mining
Douglas MembreÑ
o

Part II: Data Literacy, Licensing, and Management Challenges with TDM
Chapter 8. Framing Large Language Models: Teaching Foundational Concepts of Generative AI and Information Literacy for Critical Student Engagement
Isaac Wink and Jennifer Hootman

Chapter 9. Teaching Algorithmic Literacy for Text and Data Mining in Libraries: A Case Study at a Canadian Academic Institution
Christina Dinh Nguyen

Chapter 10. Humanities Computing, Legal Informatics, and Text Analysis Pedagogy in Italy: A Brief History of the Practice
Deborah Grbac

Chapter 11. Legal and Ethical Considerations for Curating Copyrighted Literary Collections as Data
Sarah Potvin and Alex Wermer-Colan

Chapter 12. Protecting Academic Research Opportunities: Key License Terms and Policies in Dataset Licensing
Erik Limpitlaw and Sarah Forzetting

Chapter 13. A Comparative Study of Non-Commercial Text Data Mining Policies in German Libraries
Andrea Quinn

Part III: TDM Research in Action: Practical Applications and Case Studies
Chapter 14. Library-Researcher Partnerships in Computational Social Science: Text Data Selection and Management
Amy L. Johnson

Chapter 15. Using Text Data Mining to Assess Historical Trends in Archival Description
Lia Warner

Chapter 16. Text Mining in the Archives: Preparing Materials for Using in Text Mining
Paula S. Kiser

Chapter 17. Enriching the Past: Maximizing the Value of a Congressional Hearings Corpus Using LLM Coding Tools
Jeremy Darrington

Chapter 18. TDM Reimagined: A Case Study of Leveraging Generative AI to Mine Japanese Diet Proceeding Records
Keyao Pan

Chapter 19. Text and Data Mining in Science and Engineering: Exploring Use Cases and Support Services
Ye Li

Part IV: Generating Insights from Library Reference Data
Chapter 20. Data Mining and Textual Analysis: An Approach to Efficient and Customizable Library Assessment
Crissandra George

Chapter 21. Utilizing Prodigy: Collaborative Library Assessment Projects with Advanced Natural Language Processing in Python
Jiebei Luo and Alyssa Brissett

Chapter 22. Sentiment Analysis of Online Library Reference Chat: A Cross-Site Longitudinal Comparison
Jingjing Wu, Jianqiang Wang, and Amy Jiang

Chapter 23. Emoji in Context: How to Analyze Communication, Relationships, and Behavioral Performance Through Mining Emojis in Chat Reference Transcripts
Jen-chien Yu and Lindsay Taylor

Part V: Proprietary TDM Software: Examples and Implementations
Chapter 24. Open TDM: How the Open Movement is Transforming the Way Academic Libraries Support Text and Data Mining Research
John Knox and Kate Boyd

Chapter 25. From Investigation to Implementation: Workflows for Supporting TDM Tools within the Library
Kara Handren and Sean Forbes

Chapter 26. Beyond the Tool Demonstration: An Internal Workshop to Enhance TDM Literacy Among Librarians
Brianne Dosch and Joshua Ortiz Baco
Chapter 27. Building a Text Mining Service at a University Library from the Ground Up: A Case Study ​
Using the LexisNexis Webservices API 2018-2024
Andrew Dudash and Jeffrey A. Knapp

Chapter 28. Embracing Bookness: Introducing Library Staff and Library Students to Text and Data Mining with HathiTrust Research Center
Rachel N. Hogan and Patrick Williams

Chapter 29. Multilingual Text Mining using TDM Platforms: A Librarian’
s Guide to Constellate
Jajwalya Karajgikar

Chapter 30. Evaluating Python and R Scripts from Proprietary Text Data Mining Products
Katharine Teykl

Chapter 31. Reproducible TDM examples in R and Python: A Teaching Appendix
Evan Muzzall and Anthony Weng

About the Editors and Authors