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Last Updated: 2026-02-05 16:38:03
Abstract
Network Science is a distinct domain of data science studying relations between nodes. This course is mainly concerned with methods for clustering networks, from decomposition of networks into classes of proximate or similar nodes to grouping similarly structured networks. However, methods are treated in relation to the broader context of data science in society and the study of social structure.
Objective
Students will gain insight into the application of network clustering methods with reference to the social and behavioral sciences. Through discussion and analysis of case studies, students will reflect on the social phenomena and questions of social structure and behavior that can be investigated with these methods, and will appreciate the difficulties that arise in empirical application.
Content
The following topics will be covered: * Community detection * Positional/role analysis * Generalized and stochastic blockmodeling * Network ensembles
General Information
- Language
- English
- Levels
- DS
Examination
- Type
- graded semester performance
Registration & Places
- Signup End
- 25.02.2024
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Network Clustering |
|
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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Type B: Reflection About Subject-Specific Methods and Contents (Subject-specific courses. Particularly relevant for students interested in those subjects. All these courses are also listed under the category “Typ A”, and every student can enroll in these courses.)
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