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Network Analysis
Last Updated: 2026-06-03 00:07:37
Abstract
Network science is a distinct domain of data science that is characterized by a specific kind of data being studied.While areas of application range from archaeology to zoology, we concern ourselves with social networks for the most part.Emphasis is placed on descriptive and analytic approaches rather than theorizing, modeling, or data collection.
Objective
Students will be able to identify and categorize research problems that call for network approaches while appreciating differences across application domains and contexts. They will master a suite of mathematical and computational tools, and know how to design or adapt suitable methods for analysis. In particular, they will be able to evaluate such methods in terms of appropriateness and efficiency.
Content
The following topics will be covered with an emphasis on structural and computational approaches and frequent reference to their suitability with respect to substantive theory: * Empirical Research and Network Data * Macro and Micro Structure * Centrality * Roles * Cohesion * Influence
Resources
Lecture Notes
Slides and lecture notes are distributed via the associated course moodle.
Literature
* Hennig, Brandes, Pfeffer & Mergel (2012). Studying Social Networks. Campus-Verlag. * Borgatti, Everett & Johnson (2013). Analyzing Social Networks. Sage. * Robins (2015). Doing Social Network Research. Sage. * Menczer, Fortunato & Davis (2020). A First Course in Network Science. Cambridge University Press. * Brandes & Erlebach (2005). Network Analysis. Springer LNCS 3418. * Wasserman & Faust (1994). Social Network Analysis. Cambridge University Press. * Kadushin (2012). Understanding Social Networks. Oxford University Press. * Gërxhani, De Graaf & Raub (2023). Handbook of Sociological Science. Edward Elgar.
General Information
- Language
- English
- Levels
- DS , DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Network Analysis | No time listed | 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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Doctorate Humanities, Social and Political Sciences (More Information at: )
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