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Computational Social Science
Last Updated: 2026-02-05 16:15:54
Abstract
The seminar aims at three-fold integration: (1) bringing modeling and computer simulation of techno-socio-economic processes and phenomena together with related empirical, experimental, and data-driven work, (2) combining perspectives of different scientific disciplines (e.g. sociology, computer science, physics, complexity science, engineering), (3) bridging between fundamental and applied work.
Objective
Participants of the seminar should understand how tightly connected systems lead to networked risks, and why this can imply systems we do not understand and cannot control well, thereby causing systemic risks and extreme events. They should also be able to explain how systemic instabilities can be understood by changing the perspective from a component-oriented to an interaction- and network-oriented view, and what fundamental implications this has for the proper design and management of complex dynamical systems. Computational Social Science and Global Systems Science serve to better understand the emerging digital society with its close co-evolution of information and communication technology (ICT) and society. They make current theories of crises and disasters applicable to the solution of global-scale problems, taking a data-based approach that builds on a serious collaboration between the natural, engineering, and social sciences, i.e. an interdisciplinary integration of knowledge.
Resources
Literature
Ball: Why Society Is A Complex Matter • Helbing: Social Self-Organization • Helbing: Managing Complexity • Colander/Kupers: Complexity and the Art of Public Policy • Mitchell: Complexity • Buckley: Society – A Complex Adaptive System • Castellani/Hafferty: Sociology and Complexity Science • Mikhailov/Calenbuhr: From Cells to Society • Mainzer: Thinking in Complexity • Sawyer: Social Emergence • Books published by the Santa Fe Institute Computational Social Science https://science.sciencemag.org/content/sci/323/5915/721.full.pdf Manifesto of Computational Social Science https://link.springer.com/article/10.1140/epjst/e2012-01697-8 Social Self-Organisation https://www.springer.com/gp/book/9783642240034 How simple rules determine pedestrian behaviour and crowd disasters https://www.pnas.org/content/108/17/6884.short Peer review and competition in the Art Exhibition Game https://www.pnas.org/content/113/30/8414.short Generalized network dismantling https://www.pnas.org/content/116/14/6554.short Computational Social Science: Obstacles and Opportunities https://science.sciencemag.org/content/369/6507/1060?rss%253D1= Bit by Bit: Social Research in the Digital Age https://www.amazon.co.uk/Bit-Social-Research-Digital-Age-ebook/dp/B072MPFXX2/ Further literature will be recommended in the lectures.
General Information
- Language
- English
- Levels
- DS , DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 40
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar | Computational Social Science |
|
2 h weekly |
Offered In
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Science in Perspective (In “Science in Perspective”-courses students learn to reflect on ETH’s STEM subjects from the perspective of humanities, political and social sciences. Only the courses listed below will be recognized as "Science in Perspective" courses.)
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Type A: Enhancement of Reflection Competence (SiP courses are recommended for bachelor students after their first-year examination and for all master- or doctoral students. All SiP courses are listed in Type A. Courses listed under Type B are only recommendations for enrollment for specific departments.)
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Doctorate Humanities, Social and Political Sciences (More Information at: )
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