Books

Alvarez, R. M. (Ed.). (2016). Computational social science. Cambridge University Press.

Nelimarkka, M. (2022). Computational thinking and social science: Combining programming, methodologies and fundamental concepts. Sage Publications.

Engel, U., Quan-Haase, A., Liu, S., & Lyberg, L. (Eds.). (2021). Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods. Taylor & Francis.

Welker, M., Stützer, C. M., & Egger, M. (Eds.). (2018). Computational social science in the age of big data: concepts, methodologies, tools, and applications. Herbert von Halem Verlag.

Articles

Bravo, G., Farjam, M. (2017) Prospects and challenges for the computational social sciences. Journal of universal computer science (Online), 23(11): 1057-1069.

Cabanas-Tirapu, O., Danús, L., Moro, E., Sales-Pardo, M., & Guimerà, R. (2025). Human mobility is well described by closed-form gravity-like models learned automatically from data. Nature Communications, 16(1), 1336.

Collins, A., Koehler, M., & Lynch, C. (2024). Methods that support the validation of agent-based models: An overview and discussion. Journal of Artificial Societies and Social Simulation, 27(1). (Webinar here – YouTube)

Folgado, M. G., & Sanz, V. (2022). Exploring the political pulse of a country using data science tools. Journal of Computational Social Science, 5(1), 987-1000.

Gleditsch, K. S., & Weidmann, N. B. (2012). Richardson in the information age: Geographic information systems and spatial data in international studies. Annual Review of Political Science, 15(1), 461-481.

Shi, F., & Evans, J. (2023). Surprising combinations of research contents and contexts are related to impact and emerge with scientific outsiders from distant disciplines. Nature Communications, 14(1), 1641.

Stier, A. J., Sajjadi, S., Karimi, F., Bettencourt, L. M., & Berman, M. G. (2024). Implicit racial biases are lower in more populous more diverse and less segregated US cities. Nature Communications, 15(1), 961.

Ueshima, A., Jones, M. I., & Christakis, N. A. (2024). Simple autonomous agents can enhance creative semantic discovery by human groups. Nature Communications, 15(1), 5212.

van den Berg, P., Vu, T., & Molleman, L. (2024). Unpredictable benefits of social information can lead to the evolution of individual differences in social learning. Nature Communications, 15(1), 5138.