About this site
What it is, how to cite it, and why these URLs will not move
This is the companion website to Computational & AI-Assisted Methods for Social Sciences: A Research Design Primer by Ji Ma (SAGE).
Use it to find the materials for a chapter: setup instructions, technique primers, tool guides, the studies database, worked notebooks, sample data, and project templates. These pages and downloads are free to access without an account. Linked services, such as hosted notebooks and model APIs, have their own access requirements.
The division of labour between the book’s theory chapters, its exercise chapters, and this site is set out on the home page.
URL stability policy
A printed URL cannot be corrected, so addresses cited in the book will remain available for the life of the edition:
- Cited paths never move. Every address referenced in the book is listed in a manifest that the site’s build checks on every deploy. If a page is reorganized, a redirect stays at the old address.
- Content is updated. Tool guides change as software changes; each carries a “last reviewed” date.
- The site is versioned. The footer identifies the source revision used to build it.
- Download paths are checked too. The build checks dataset and notebook addresses, including those not cited in print.
An archival deposit on Zenodo is planned to preserve a citable snapshot at publication. Its DOI will be added here when available.
How to cite
Ma, J. (2026). Computational & AI-Assisted Methods for Social Sciences: A Research Design Primer [Companion website]. https://cssprimer.org
For a specific page, add the page title and the date you accessed it.
Reuse
Site text and code examples may be reused for teaching and research with attribution. Linked tools and cited works carry their own licenses.
Acknowledgements
This book grew out of a graduate course I have taught since 2019, and it carries the marks of everyone who worked through it with me. My students were its first and most demanding readers. Every exercise was tested in class, and most were rewritten because a student asked a question I could not answer well.
My thanks to:
- Fall 2019: Ryan R. Anderson, Xiao Han, Wenkang Li, Alex A. Meed, Andrew Messamore, Temitope Steph Oladimeji, Lucas L. Sepulveda, Ethan Tenison, Mychal Warner, and Harshal Zalke.
- Spring 2023: John-Patrick O. Akinyemi, Rachael E. Boyle, En-Yu Li, Zander Mintz, Whitney Nelson, Terrence Neumann, Junyeon Rhee, Nathaniel F. Stern, Ziyi Wang, and Amy Zhang.
- Spring 2024: Guadalupe Selinda Cantu, Yug Dave, Isabella L. Peterson, Zain Raza, and Ryotaro Takehara.
- Spring 2025: Ali Altahafi, Yuan Gao, Mara Luz Gomez, Yuting He, Angjelin A. Hila, Melissa Ionson, Tianhao Li, Katherine Isa Richardson, and Robert Allen Stein.
- Spring 2026: Yilun Ai, Cheng Chow, Kieran T. Givens, Xiuer Gu, Benjamin G. Hickman, Inchan Hwang, Chengkang Li, Enqi Li, Blake Marlowe, Balmukund Sharma, Haoyang Wang, and Jiayu Wang.
Chenxin Zhang, Meiying Xu, and Jun Zhang worked as my research assistants, compiling the studies database and the reference collection behind it through many rounds of checking that were more tedious than the results make them look.
AI-use disclosure
This website was prepared from the book’s contents with the help of generative AI tools (Codex and Claude Code).
Colophon
The site is built with Quarto and published through GitHub Pages. Worked outputs are saved from earlier runs. The notebook notes describe the data and software you need if you want to rerun those examples.
Contact and corrections
Corrections go through the errata page.