Ulrik Brandes: Catalogue data in Autumn Semester 2018
|Name||Prof. Dr. Ulrik Brandes|
Professur für Soziale Netzwerke
ETH Zürich, WEP J 14
|Telephone||+41 44 632 21 96|
|Department||Humanities, Social and Political Sciences|
|851-0252-04L||Behavioral Studies Colloquium||2 credits||2K||U. Brandes, V. Amati, H.‑D. Daniel, D. Helbing, C. Hölscher, M. Kapur, R. Schubert, C. Stadtfeld, E. Stern|
|Abstract||This colloquium offers an opportunity for students to discuss their ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. It also offers an opportunity for students from other disciplines to discuss their research ideas in relation to behavioral science. The colloquium also features invited research talks.|
|Objective||Students know and can apply autonomously up-to-date investigation methods and techniques in the behavioral sciences. They achieve the ability to develop their own ideas in the field and to communicate their ideas in oral presentations and in written papers. The credits will be obtained by a written report of approximately 10 pages.|
|Content||This colloquium offers an opportunity for students to discuss their ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. It also offers an opportunity for students from other disciplines to discuss their ideas in so far as they have some relation to behavioral science. The possible research areas are wide and may include theoretical as well as empirical approaches in Social Psychology and Research on Higher Education, Sociology, Modeling and Simulation in Sociology, Decision Theory and Behavioral Game Theory, Economics, Research on Learning and Instruction, Cognitive Psychology and Cognitive Science. Ideally the students (from Bachelor, Master, Ph.D. and Post-Doc programs) have started to start work on their thesis or on any other term paper. |
Course credit can be obtained either based on a talk in the colloquium plus a written essay, or by writing an essay about a topic related to one of the other talks in the course. Students interested in giving a talk should contact the course organizers (Ziegler, Kapur) before the first session of the semester. Priority will be given to advanced / doctoral students for oral presentations. The course credits will be obtained by a written report of approximately 10 pages. The colloquium also serves as a venue for invited talks by researchers from other universities and institutions related to behavioral and social sciences.
|851-0252-07L||Open Debates in Social Network Research |
Number of participants limited to 30
|2 credits||2S||C. Stadtfeld, U. Brandes, A. Vörös|
|Abstract||Social network research develops through contributions from many scientific disciplines. Among others, scholars of sociology, psychology, political science, computer science, physics, mathematics, and statistics have advanced theories and methods in this field - promoting multiple perspectives on important problems. This course aims to present and structure open debates in social network research.|
|Objective||Research on social networks has developed as a highly interdisciplinary field. By the end of this seminar, students will be able to identify and compare different discipline- and subject-specific approaches to social network research (coming from, e.g., sociology, psychology, political science, computer science, physics, mathematics, and statistics). They will be familiar with recent publications in the field of social networks and be able to critically participate in a number of open debates in the field. Among others, these debates are centered around the types and measurement of social relations across different contexts, the importance of simple generative processes in shaping network structure, the role of social selection and influence mechanisms in promoting segregation and polarization, and the development of statistical models for the analysis of dynamic networks.|
Particularly suitable for students of D-INFK, D-MATH
|3 credits||2V||U. Brandes|
|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
|Lecture notes||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.
* 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.
|851-0252-16L||Literature Networks||3 credits||2S||U. Brandes|
|Abstract||We study applications of network science methods in the domain of literature.|
Topics are selected for diversity in research questions and techniques
including text networks from word-level similarities,
character networks, and correspondences.
The Deutscher Novellenschatz (1871-1876) corpus
will provide an opportunity for replications in a shared context.
|Objective||Network science as a paradigm is entering domains from engineering to the humantities|
but application is tricky.
By examples from recent research in the digital humanities,
students learn to appreciate that, and how, context matters.
They will be able to assess the appropriateness of approaches
for substantive research problems,
and especially when and why quantitative approaches are or are not suitable.
|851-0252-17L||Network Analysis Lab (with Exercises) |
Only for Data Science MSc.
|5 credits||2V + 1U||U. Brandes|
|Abstract||This is a voluntary supplement for the course Network Analysis.|
|Objective||Deeper understanding of mathematical principles|
and practical applications of the methods underlying network analysis.