The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. Two chapters were made with GESIS participation.
U. Engel, A. Quan-Haase, S. Xun Liu, & L.E. Lyberg (2022). Handbook of Computational Social Science. Volume 1 Theory, Case Studies and Ethics. Routledge. ISBN 9780367456528 https://www.routledge.com/Handbook-of-Computational-Social-Science-Volume-1-Theory-Case-Studies/Engel-Quan-Haase-Liu-Lyberg/p/book/9780367456528
U. Engel, A. Quan-Haase, S. Xun Liu, & L.E. Lyberg (2022). Handbook of Computational Social Science. Volume 2 Data Science, Statistical Modelling, and Machine Learning Methods. Routledge. ISBN 9781032077703 https://www.routledge.com/Handbook-of-Computational-Social-Science-Volume-2-Data-Science-Statistical/Engel-Quan-Haase-Liu-Lyberg/p/book/9781032077703