An awesome curated list of resources for Computational Social Science.
Inspired by Awesome Network Analysis and others.
The order of entries within categories is either alphabetically or
chronologically.
Please add your resources according to the respective ordering
- Books
- Conferences
- Education
- Research Groups
- Journals
- Selected Papers
- Software
- Miscellaneous
- Relevant Awesome Lists
- Contributing
Entries are ordered chronologically
- Growing Artificial Societies: Social Science from the Bottom Up, by 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)
- 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)
- 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)
- 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)
- 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)
Relevant conferences where the community (or parts thereof) meets
- BigSurv - Big Data Meets Survey Science
- CHI - ACM CHI Conference on Human Factors in Computing Systems
- Complex Networks - International Conference on Complex Networks and their Applications
- COMPTEXT Conference
- Conference on Complex Systems, in particular the Computational Social Science satellite
- EPSA - European Political Science Association Conference (Methods division)
- IC2S2 - The International Conference for Computational Social Science
- ICA - Annual International Communication Association Conference (Methods Division)
- ICWSM - International AAAI Conference on Web and Social Media
- NetSci - International Conference on Network Science
Computational Social Science Events Worldwide, Public Calendar
Learning material/courses tailored towards Computational Social Science
See also the Software section for material on software tools
- SAGE collection of teaching material for Computational Social Science - Large collection of various teaching material for Computational Social Science
- Social and Economic Networks: Models and Analysis - Online course on social and economic networks taught by Matthew O. Jackson
- Toolkit for Digital Methods - A wiki of resources for digital methods in Social Sciences
- Introduction to computational social science, by Matthew J. Salganik, Princeton University (2019)
- A gentle introduction to network science, by Renaud Lambiotte, University of Oxford (2018)
- Essex Summer School in Social Science Data Analysis
- GESIS Fall Seminar in Computational Social Science
- The Summer Institutes in Computational Social Science
- Topics in Digital and Computational Demography, PhD level, one week course.
Bachelor, Master, PhD programs (alphabetically by country)
- Master Computational Social System, TU Graz, Austria
- Master of Arts in Political Science with Focus on Computational Social Sciences, University of Bamberg, Germany
- Master Social and Economic Data Science, University of Konstanz, Germany
- Bachelor Computational Social Science at the University of Amsterdam, Netherlands
- Master Computational Social Science, Koç University, Turkey
- Master Computational Social Systems, RWTH Aachen, Germany
Alphabetially by country and city)
- Digital Humanities Lab at UFBA, Salvador, Brazil
- CSS Lab TU Graz, Graz, Austria
- Copenhagen Center for Social Data Science (SODAS), Copenhagen, Denmark
- NEtwoRks, Data, and Society (NERDS), Copenhagen, Denmark
- CSS Lab RWTH Aachen, Aachen, Germany
- CSS Department at GESIS, Cologne, Germany
- Department of Digital and Computational Demography, Rostock, Germany
- Behave Lab, Milan, Italy
- Institute for Cross-Disciplinary Physics and Complex Systems (IFISC), Palma, Spain
- Social Networks Lab, Zürich, Switzerland
- Data Science and AI Lab, Abu Dhabi, UAE
- Oxford Internet Institute, Oxford, UK
- Observatory on Social Media, Indiana University, Bloomington, USA
- Lazerlab, Northeastern University, Boston, USA
- Computational Social Science Institute at UMass, Massachusetts Amherst, USA
- Computational Communication Research
- EPJ Data Science
- Journal of Computational Social Science
- Journal of Artificial Societies and Social Simulation
- Nature Human Behavior
- Social Science Computer Review
- Social Media and Society
Important papers for/about the field, not specific research. Ordered chronologically.
- From Factors to Actors: Computational Sociology and Agent-Based Modeling by Michael W. Macy and Robert Willer (2002)
- Life in the network: the coming age of computational social science by David Lazer et al. (2009)
- Critical Questions for Big Data by Dana Boyd and Kate Crawford (2012)
- A 61-million-person experiment in social influence and political mobilization by Robert M. Bond et al. (2012)
- Manifesto of computational social science by R. Conte, N. Gilbert, G. Bonelli, C. Cioffi-Revilla, G. Deffuant, J. Kertesz, V. Loreto, S. Moat, J. -P. Nadal, A. Sanchez, A. Nowak, A. Flache, M. San Miguel & D. Helbing (2012)
- Digital Footprints: Opportunities and Challenges for Online Social Research by Scott A. Golder and Michael W. Macy (2014)
- Sociology in the Era of Big Data: The Ascent of Forensic Social Science by Daniel A. McFarland, Kevin Lewis & Amir Goldberg (2016)
- Installing computational social science: Facing the challenges of new information and communication technologies in social science by Raphael H. Heiberger & Jan R. Riebling (2016)
- Computational Social Science Methodology, Anyone? by Joop J. Hox (2017)
- The empiricist’s challenge: Asking meaningful questions in political science in the age of big data by Andreas Jungherr and Yannis Theocharis (2017)
- Computational Social Science ≠ Computer Science + Social Data by Hanna Wallach (2018)
- When Communication Meets Computation: Opportunities, Challenges, and Pitfalls in Computational Communication Science by Wouter van Atteveldt and Tai-Quan Peng (2018)
- Analytical sociology and computational social science by Keuschnigg, M., Lovsjö, N. & Hedström, P. (2018)
- Computation and the Sociological Imagination by James Evans and Jacob G. Foster (2019)
- Machine Learning for Sociology by Mario Molina and Filiz Garip (2019)
- Computational social science: Obstacles and opportunities by David Lazer et al. (2020) (open access version)
- Computational Social Science and the Study of Political Communication by Yannis Theocharis and Andreas Jungherr (2020)
- Computational Social Science and Sociology by Achim Edelmann, Tom Wolff, Danielle Montagne and Christopher A. Bail (2020)
- Measuring algorithmically infused societies by Claudia Wagner, Markus Strohmaier, Alexandra Olteanu, Emre Kıcıman, Noshir Contractor & Tina Eliassi-Rad (2021)
- The data revolution in social science needs qualitative research by Nikolitsa Grigoropoulou & Mario L. Small (2022)
Focus on accessible introduction into computational tools, preferably open source material
- Awesome R for general resources in R
- Awesome Python (other lists: 1, 2, 3) for general resources in Python
- APIs for Social Scientists
- Introduction to Computational Social Science in R
- Introduction to Computational Social Science Methods with Python
Resources that do not fit into other categories
- Awesome Causality
- Awesome Community Detection
- Awesome Data Science
- Awesome Data Science with Python (another)
- Awesome Data Visualization
- Awesome Deep Learning
- Awesome Digital Humanities
- Awesome Jupyter
- Awesome Machine Learning
- Awesome MySQL
- Awesome Network Analysis
- Awesome NLP (another one)
- Awesome Notebooks
- Awesome Open Science
- Awesome Python (other lists: 1, 2, 3)
- Awesome R
- Awesome Julia
- Awesome Research Software Registries
- Awesome Scholarly Data Analysis
- Awesome Quarto
Contributions welcome! Read the contribution guidelines first.