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
  • 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

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)
• Computational Thinking and Social Science, by Matti Nelimarkka (2023)

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
• SSC - Social Simulation Conference
• WebSci - ACM Web Science Conference

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

• 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.

• 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)

• BIGSSS Computational Social Science Summer Schools
• Edinburgh Data and Text Analysis Summer School
• ESSA (European Social Simulation Association) 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.

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

• BA/BSc in Data Science and Society (DSS), Central European University, AUT
• B.Sc. Social Data Science, Witten/Herdecke University, DEU
• BSc Social Sciences with Data Science, University College London, GBR
• Bachelor of Social Sciences in Data Science and Policy Studies, Chinese University of Hong Kong, HKG
• Bachelor Computational Social Science, University of Amsterdam, NLD
• BS in Social Data Science, University of Maryland, USA
• BS in Social Data Analytics, Pennsylvania State University, USA
• BS in Computational Social Science, University of Pittsburgh, USA

• 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
• MSc in Computational Social Science, Chinese University of Hong Kong (Shenzhen), CHN
• Master of Data Science for Public Policy, Hertie School, DEU
• Master Social and Economic Data Science, University of Konstanz, DEU
• Mannheim Master in Social Data Science, University of Mannheim, 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
• Master of Contemporary Societies, track on social data science, University of Helsinki, FIN
• 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
• 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
• MSc/PG Diploma Applied Social Data Science, Trinity College Dublin, IRE
• Master Data Science for Economics, University of Milan, ITA
• Master in Social Data Science, University of Milano-Bicocca, ITA
• Master in Social Sciences for a Digital Society, Vrije Universiteit Amsterdam, NLD
• Master's Programme Computational Social Science, Linköping University, SWE
• Master Computational Social Science, Koç University, TUR
• Master of Computational Social Science (MaCSS), University of California Berkeley, USA
• 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
• Master of Arts in Interdisciplinary Studies: Computational Social Science Concentration, 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
• 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

• PhD in Computational Social Science, Chinese University of Hong Kong (Shenzhen), CHN
• DPhil Social Data Science, University of Oxford, GBR
• PhD Quantitative and Computational Social Science, University College Dublin, IRE
• PhD in Information, University of Michigan, Ann Arbor, USA
• Complex Networks and Systems track of the PhD in Informatics, Indiana University, Bloomington, USA
• Network Science PhD Program, Northeastern University, Boston, USA
• PhD in Information Science, University of Colorado, Boulder, USA
• PhD Program in Social & Engineering Systems (SES), Massachusetts Institute of Technology, Cambridge, USA
• PhD in Information Sciences, University of Illinois, Champaign, USA
• Doctor of Philosophy in Information Studies (PhD), University of Maryland, College Park, USA
• Ph.D. in Information Science, University of California, Berkeley, USA
• Doctoral Program in Communication, University of California, Davis, USA
• Ph.D. Specialization in Computational Social Science, University of California, San Diego, USA
• Ph.D. in Information and Media, Michigan State University, East Lansing, USA
• Ph.D. in Information Technology Management, Michigan State University, East Lansing, USA
• PhD in Media, Technology, and Society (MTS), Northwestern University, Evanston, USA
• Dual Ph.D. Program in Computer Science and Communication: Technology and Social Behavior (TSB), Northwestern University, Evanston, USA
• PhD Program at the Kellogg School of Management, Northwestern University, Evanston, USA
• PhD in Computational Social Science, George Mason University, Fairfax, USA
• Ph.D. in Communication and Information Sciences, University of Hawaii at Manoa, Honolulu, USA
• Information Science Ph.D. program, Cornell University, Ithaca, USA
• Doctoral Program in Industrial & Systems Engineering (ISE), University of Southern California, Los Angeles, USA
• Communication (PhD), University of Southern California, Los Angeles, USA
• Ph.D. Program in Communication, Information, and Media, Rutgers University, New Brunswick, USA
• Ph.D. Specialization in Data Science, Columbia University, New York, USA
• Doctorate in Communication, University of Pennsylvania, Philadelphia, USA
• PhD in Societal Computing, Carnegie Mellon University, Pittsburgh, USA
• Doctorate in Informaiton Science, University of Washington, Seattle, USA
• PhD degree in Management Science and Engineering (MS&E), Stanford University, USA
• PhD in Information, University of Arizona, Tucson, USA

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
• Institute of Computational Social Science, CUHK-Shenzhen, CHN
• CSS Lab RWTH Aachen, Aachen, DEU
• Data Science Lab, Hertie School, Berlin, DEU
• CSS Department at GESIS, Cologne, DEU
• Chair of Data Science in the Economic and Social Sciences, Mannheim, 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
• Social Data Science Lab at Cardiff University, Cardiff, GBR
• 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
• RC2S2 Research Center for Computational Social Science, Eötvös Loránd University, Budapest, HUN
• 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
• Viral Lab (VRLLab), Sabanci 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
• Al-Adala Lab, University of Colorado, Boulder, USA
• Colorado Laboratory for Users, Media, and Networks (COLUMN), University of Colorado, Boulder, USA
• MIT Institute for Data, Systems, and Society (IDSS), Massachusetts Institute of Technology, Cambridge, USA
• Center for Spatial Data Science (CSDS), University of Chicago, Chicago, USA
• Knowledge Lab, University of Chicago, Chicago, USA
• Social Data Science Center (SoDa), University of Maryland, College Park, USA
• MESO (Modeling Emergent Social Order) Lab, Ohio State University, Columbus, USA
• Computational Communication Research Lab (C^2 or C-square), University of California, Davis, USA
• Quello Center, Michigan State University, East Lansing, USA
• Computational Journalism Lab, Northwestern University, Evanston, USA
• Delta Lab, Northwestern University, Evanston, USA
• Lab on Innovation, Networks, and Knowledge (LINK), Northwestern University, Evanston, USA
• People, Space, and Algorithms (PSA) Research Group, Northwestern University, Evanston, USA
• Science of Networks in Communities (SONIC) Lab, Northwestern University, Evanston, USA
• Center for AI in Society(CAIS), University of Southern California, Los Angeles, USA
• Computational Social Science Laboratory, University of Southern California, Los Angeles, USA
• HUmans | MAchines | Networks | Society Lab (HUMANS), University of Southern California, Los Angeles, USA
• Computational Social Science Institute at UMass, Massachusetts Amherst, USA
• Computational Social Science Lab, Rutgers University, New Brunswick, USA
• Working Group on Computational Social Science, Columbia University, New York, USA
• Center for Social Media and Politics (CSMaP), New York Univiersity, New York, USA
• Center for Information Networks and Democracy(CIND), University of Pennsylvania, Philadelphia, USA
• Computational Social Science Lab (CSSLab), University of Pennsylvania, Philadelphia, USA
• Network Dynamics Group, University of Pennsylvania, Philadelphia, 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
• Santa Fe Institute (SFI), Santa Fe, USA
• Community Data Science Collective, University of Washington, Seattle, 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

Ordered alphabetically

• Big Data & Society
• Computational Communication Research
• Computational Economics
• EPJ Data Science
• Frontiers in Big Data
• Information, Communication & Society
• Journal of Artificial Societies and Social Simulation
• Journal of Computational Social Science
• Journal of Quantitative Description: Digital Media
• Journal of Social Computing
• Nature Human Behavior
• New Media & Society
• Social Media and Society
• Social Science Computer Review

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)

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
• Quanteda Tutorials for Quantitative Text Analysis in R
• R Course Material for Communication Science

Resources that do not fit into other categories

• Google Group Computational Social Science Network
• Podcast about Computational Communication Science
• RatSWD publication "Big data in social, behavioural, and economic sciences: Data access and research data management (Including an expert opinion on "Web scraping in independent academic research")"
• reddit community "CompSocial"

• Awesome Causality
• Awesome Community Detection
• Awesome Data Science with Python (another)
• Awesome Data Science
• 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 Quarto
• Awesome R
• Awesome Research Software Registries
• Awesome Scholarly Data Analysis

Contributions welcome! Read the contribution guidelines first.