Computational Social Science seminar series
Fall Semester 2016
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.
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.
Important: Course material is intended for personal use in the context of this course only; redistributing, citing or publishing any of the material is strictly prohibited. If prompted, please enter your ETH username and password to download course materials.
The course will cover a range of topics in Computational Social Science. The following 5 core readings should give you a good first impression of the topic - we strongly recommend you to read them before the start of the class:
- D. Brockmann and D. Helbing. The hidden geometry of complex, network-driven contagion phenomena. Science, 342(6164):1337–1342, 2013.
- D. Easley and J. Kleinberg. Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press, 2010.
- D. Helbing. Globally networked risks and how to respond. Nature, 497(7447):51–59, 2013.
- D. Lazer, A. Pentland, L. Adamic, S. Aral, A. L. Barabasi, D. Brewer, N. A. Christakis, N. Con- tractor, J. H. Fowler, M. Gutmann, T. Jebara, G. King, M. Macy, D. Roy, and M. Van Alstyne. Computational Social Science. Science, 323, Feb. 2009
- H. P. Young. Condorcet’s Theory of Voting. American Political Science Review, 82(04):1231– 1244, 1988.
Please also note that there may be additional readings for some of the seminar presentations. Those will be linked directly from the course schedule below.
|26.09.||Prof. Dr. Dr. Dirk Helbing
|03.10.||Dr. Rebekka Buchholz|
|31.10.||Dr. Juri Viehoff
|14.11.||Dr. Sandra Andraszewicz (tbc)
|21.11.||Dr. Karsten Donnay
|05.12.||Prof. Dr. Alessandro Lomi (tbc)