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Computational Social Science Books

Below is a sample of computational social science books available for purchase. Some are introductory to the field, others are more methodological in orientation. They are listed in alphabetical order and are largely taken from Awesome Computational Social Science. Each title provides a unique perspective and depth of knowledge on the subject. Whether you’re a beginner or an expert, there’s something here for everyone. Exploring these books will undoubtedly enhance your understanding of the intricate dynamics of computational social science.

• Growing Artificial Societies: Social Science from the Bottom Up, by Joshua M. Epstein and Robert L. Axtell (1996)
• Six Degrees: The Science of a Connected Age, by Duncan J. Watts (2004)
• Networks, Crowds, and Markets: Reasoning About a Highly Connected World, by David Easley and Jon Kleinberg (2010)
• Everything is Obvious, by Duncan J. Watts (2011)
• Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science, by Joshua M. Epstein (2014)
• Social Phenomena: From Data Analysis to Models, edited by Bruno Gonçalves, Nicola Perra (2015)
• Computational Social Sciences, Springer book series (2015-2023)
• Big Data Is Not a Monolith, edited by Cassidy R. Sugimoto, Hamid R. Ekbia, and Michael Mattioli (2016)
• Bit By Bit: Social Research in the Digital Age, by Matthew J. Salganik (2017)
• Decoding the Social World: Data Science and the Unintended Consequences of Communication, by Sandra González-Bailón (2017)
• Digital Sociology: The Reinvention of Social Research, by Noortje Marres (2017)
• How Behavior Spreads: The Science of Complex Contagions, by Damon Centola (2018)
• The Model Thinker: What You Need to Know to Make Data Work for You, by Scott E. Page (2018)
• What is Digital Sociology?, by Neil Selwyn (2019)
• The Oxford Handbook of Networked Communication, edited by Brooke Foucault Welles and Sandra González-Bailón (2020)
• Research Exposed: How Empirical Social Science Gets Done in the Digital Age, edited by Eszter Hargittai (2020)
• Retooling Politics: How Digital Media Are Shaping Democracy, by Andreas Jungherr, Gonzalo Rivero, and Daniel Gayo-Avello (2020)
• Sociologia Digital: uma breve introdução, by Leonardo Nascimento (2020)
• A First Course in Network Science, by Filippo Menczer, Santo Fortunato, Clayton A. Davis (2020)
• How Humans Judge Machines, by Cesar A. Hidalgo, Diana Orghian, Jordi Albo Canals, Filipa De Almeida, Natalia Martin (2021)
• The Science of Science, by Dashun Wang and Albert-László Barabási (2021)
• Doing Computational Social Science - A Practical Introduction, by John McLevey (2021)
• Big Data and Social Science: Data Science Methods and Tools for Research and Practice, 2nd Edition, by Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter and Julia Lane (2021)
• Text as Data: A New Framework for Machine Learning and the Social Sciences,, by Justin Grimmer, Margaret E. Roberts, and Brandon M. Stewart (2022)
• Computational Analysis of Communication, by Wouter van Atteveldt, Damian Trilling, and Carlos Arcila Calderon (2022)
• The SAGE Handbook of Social Media Research Methods, edited by Anabel Quan-Haase and Luke Sloan (2022)
• Handbook of Computational Social Science Volume 1 & 2, edited by Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu, Lars Lyberg (2022)
• Research Handbook on Digital Sociology, edited by Jan Skopek (2023)
• Handbook of Computational Social Science for Policy, by Eleonora Bertoni, Matteo Fontana, Lorenzo Gabrielli, Serena Signorelli, Michele Vespe (2023)
• Computational Thinking for Social Scientists, by Jae Yeon Kim (2023)

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