Awesome Computational Social Science

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
- R
- Python
- Tutorials
Miscellaneous
Relevant Awesome Lists
Contributing

Books

Entries are ordered chronologically

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)

Conferences

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
CSCW - ACM Conference On Computer-Supported Cooperative Work
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

Education

Learning material/courses tailored towards Computational Social Science

Online Courses and Material

See also the Software section for material on software tools

CSC2552 Topics in Computational Social Science: AI, Data, and Society - Seminar course taught by Ashton Anderson at the University of Toronto, Canada.
NLP+CSS 201 Tutorials - Tutorials for advanced natural language processing methods designed for computational social science research.
SAGE collection of teaching material for Computational Social Science - Large collection of various teaching material for Computational Social Science
SICSS Learning Materials - Open source teaching and learning resources 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
UCCSS: University of California Computational Social Science - Multidisciplinary, multi-perspective, and multi-method guide on how to better understand society and human behavior with modern research tool.

Videos and Lectures

A gentle introduction to network science, by Renaud Lambiotte, University of Oxford (2018)
Introduction to computational social science, by Matthew J. Salganik, Princeton University (2019)
Python for Computational Social Science and Digital Humanities, by Christopher Cameron, Cornell University (2023)

Workshops

BIGSSS Computational Social Science Summer Schools
Edinburgh Data and Text Analysis Summer School
Essex Summer School in Social Science Data Analysis
GESIS Fall Seminar in Computational Social Science
Mediterranean School of Complex Networks
NLP + CSS: a series of workshops on natural language processing (NLP) and computational social science (CSS).
The Summer Institutes in Computational Social Science
Topics in Digital and Computational Demography, PhD level, one week course.

University Course Programs

Bachelor, Master, PhD programs (alphabetically by country using ISO 3166-1 alpha 3 codes)

Master Computational Social System, TU Graz, AUT
Master of Science program in Social Data Science, Central European University, AUT
Master of Sociology: Quantitative Analysis and Social Data Science specialisation, KU Leuven, BEL
Master in Computational Social Sciences at the University of Lucerne, CHE
Master of Data Science for Public Policy, Hertie School, DEU
Master Social and Economic Data Science, University of Konstanz, DEU
M.Sc. Quantitative Data Science Methods: Psychometrics, Econometrics and Machine Learning, University of Tübingen, DEU
~~Master Computational Social Systems~~ (This course of study is being phased out), RWTH Aachen, DEU
Master of Science (MSc) in Social Data Science, University of Copenhagen, DNK
Master in Computational Social Science, Universidad Carlos III de Madrid, ESP
MSc&T “Data and Economics for Public Policy”, Institut Polytechnique de Paris, FRA
Master in Data Science for Social Sciences, Toulouse School of Economics, FRA
MSc Applied Social Data Science, London School of Economics and Political Science, GBR
MPA in Data Science for Public Policy, London School of Economics and Political Science, GBR
MSc Social and Geographic Data Science, University College London, GBR
MSc Data Science and Public Policy, University College London, GBR
MSc Human and Social Data Science, University of Sussex, GBR
MSc Social Data Science, University of Exeter, GBR
MSc Social Data Science, University of Oxford, GBR
DPhil Social Data Science, University of Oxford, GBR
Bachelor of Social Sciences in Data Science and Policy Studies, Chinese University of Hong Kong, HKG
Bachelor of Arts and Sciences in Social Data Science, University of Hong Kong, HKG
Masters in Computational Social Science, Indian Institute of Technology (IIT) Jodhpur, IND
Master Politics and Data Science, University College Dublin, IRE
MSc Social Data Science, University College Dublin, IRE
PhD Quantitative and Computational Social Science, University College Dublin, IRE
MSc/PG Diploma Applied Social Data Science, Trinity College Dublin, IRE
Master Data Science for Economics, University of Milan, ITA
Master (Research) in Societal Resilience - Big Data for Society, Vrije Universiteit Amsterdam, NLD
Bachelor Computational Social Science, University of Amsterdam, NLD
Master's Programme Computational Social Science, Linköping University, SWE
Master Computational Social Science, Koç University, TUR
M.S. in Computational Social Science, University of California San Diego, USA
M.A. in Computational Social Science, University of Chicago, USA
M.S. in Computational Analysis & Public Policy, University of Chicago, USA
Master of Science in Data Analytics & Computational Social Science, University of Massachusetts Amherst, USA
Complex Networks and Systems track of the PhD in Informatics, Indiana University Bloomington, USA
Master of Arts in Interdisciplinary Studies: Computational Social Science Concentration, George Mason University, USA
PhD in Computational Social Science, George Mason University, USA
Master of Science in Data Science for Public Policy, Georgetown University, USA
MA in Quantitative Methods in the Social Sciences: Data Science Focus, Columbia University, USA
BS in Social Data Science, University of Maryland, USA
Master of Science in Public Policy and Data Science, University of Southern California, USA
Master's Degree Applied Urban Science and Informatics, New York University, USA
Master of Science in Survey and Data Science, University of Michigan, USA
Master of Science in Social Policy + Data Analytics for Social Policy Certificate, University of Pennsylvania, USA
BS in Social Data Analytics, Pennsylvania State University, USA
BS in Computational Social Science, University of Pittsburgh, USA

Research Groups

Ordered alphabetically by country and city (using ISO 3166-1 alpha 3 country codes)

Data Science and AI Lab, Abu Dhabi, ARE
Computational Social Science Lab, University of Sydney, AUS
CSS Lab TU Graz, Graz, AUT
Digital Humanities Lab at UFBA, Salvador, BRA
Computational Social Science Lab, University of Toronto, Toronto, CAN
Professorship of Computational Social Science (COSS), ETH Zürich, CHE
Social Networks Lab, Zürich, CHE
Computational Communication Collaboratory, Nanjing, CHN
CSS Lab RWTH Aachen, Aachen, DEU
Data Science Lab, Hertie School, Berlin, DEU
CSS Department at GESIS, Cologne, DEU
Computational Social Science and Big Data TUM Munich, Munich, DEU
Department of Digital and Computational Demography, Rostock, DEU
Copenhagen Center for Social Data Science (SODAS), Copenhagen, DNK
NEtwoRks, Data, and Society (NERDS), Copenhagen, DNK
Computational Social Science Group, Tartu, EST
Institute for Cross-Disciplinary Physics and Complex Systems (IFISC), Palma, ESP
Centre for Social Data Science, Helsinki, FIN
Centre for Data, Culture & Society, Edinburgh, GBR
Oxford Internet Institute, Oxford, GBR
Social Data Institute, University College London, GBR
Web Mining Lab, City University of Hong Kong, Hong Kong, HKG
Computational Social Sciences and Law Lab, City University of Hong Kong, Hong Kong, HKG
Connected_Politics Lab, Dublin, IRL
Computational Social Science Centre (CSSC), Bologna, ITA
Behave Lab, Milan, ITA
Center of Data Science and Complexity for Society (CDCS), Sapienza University, Rome, ITA
Center for Computational Social Science and Human Dynamics (C2S2), University of Trento and Bruno Kessler Foundation, Trento, ITA
Mobile and Social Computing Lab (MobS Lab), Bruno Kessler Foundation, Trento, ITA
CENTAI Institute, Turin, ITA
Center for Computational Social Science, Kobe University, Kobe, JPN
Computational Social Science Lab, Tokyo Institute of Technology, Tokyo, JPN
Computational Communication Science Amsterdam, NLD
Social and Behavioural Data Science Centre, Amsterdam, NLD
UNU-MERIT Computational Innovation Lab on Crises, Transformation and Sustainable Development, Maastricht, NLD
ODISSEI (Open Data Infrastructure for Social Science and Economic Innovations), Rotterdam, NLD
Political Data Science (PODS) Research Group, Oslo, NOR
UU-InfoLab (Uppsala University Information Laboratory), Uppsala, SWE
Center for Computational Social Sciences, Koç University, Istanbul, TUR
Communication Data and Network Analytics Lab, Academia Sinica, Taipei, TWN
Observatory on Social Media, Indiana University, Bloomington, USA
Center for Complex Networks and Systems Research, Indiana University, Bloomington, USA
Soda (Social Data and AI) Lab, Indiana University, Bloomington, USA
Lazerlab, Northeastern University, Boston, USA
Laboratory for the Modeling of Biological and Socio-Technical Systems (MOBS Lab), Northeastern University, Boston, USA
Network Science Institute (NetSI), Northeastern University, Boston, USA
Social data science center, University of Maryland, College Park, USA
MESO (Modeling Emergent Social Order) Lab, Ohio State University, Columbus, USA
Computational Social Science Institute at UMass, Massachusetts Amherst, USA
Working Group on Computational Social Science, Columbia University, New York, USA
Center for Computational Analysis of Social and Organizational Systems (CASOS), Carnegie Mellon University, Pittsburgh, USA
PITT Initiative on Computational Social Science, University of Pittsburgh, Pittsburgh, USA
IRiSS Center for Computational Social Science, Stanford University, USA
Center for Social Data Analytics (C-SoDA), Pennsylvania State University, University Park, USA
Computational Social Science Lab, Purdue University, West Lafayette, USA

Journals

Ordered alphabetically

Selected Papers

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)
Social media for large studies of behavior by Derek Ruths and Jürgen Pfeffer (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)
Social data: Biases, methodological pitfalls, and ethical boundaries by Alexandra Olteanu, Carlos Castillo, Fernando Diaz and Emre Kıcıman (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)
Machine Learning for Social Science: An Agnostic Approach by Justin Grimmer, Margaret E. Roberts, and Brandon M. Stewart (2021)
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)

Software

Focus on accessible introduction into computational tools, preferably open source material

gesiscss/awesome-computational-social-science

gesiscss

Reviews

Repository Details

Awesome Computational Social Science

Contents

Books

Conferences

Education

Online Courses and Material

Videos and Lectures

Workshops

University Course Programs

Research Groups

Journals

Selected Papers

Software

R

Python

Tutorials

Miscellaneous

Relevant Awesome Lists

Contributing

More Repositories