Ulrik Brandes: Katalogdaten im Herbstsemester 2020

NameHerr Prof. Dr. Ulrik Brandes
NamensvariantenUlrik Brandes
LehrgebietSoziale Netzwerke
Adresse
Professur für Soziale Netzwerke
ETH Zürich, WEP J 14
Weinbergstr.109
8092 Zürich
SWITZERLAND
Telefon+41 44 632 21 96
E-Mailubrandes@ethz.ch
DepartementGeistes-, Sozial- und Staatswissenschaften
BeziehungOrdentlicher Professor

NummerTitelECTSUmfangDozierende
851-0252-04LBehavioral Studies Colloquium Information 0 KP2KD. Helbing, U. Brandes, C. Hölscher, M. Kapur, C. Stadtfeld, E. Stern
KurzbeschreibungThis colloquium is about recent and ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science. It features invited presentations from internal and external researchers as well as presentations of doctoral students close to submitting their dissertation research plan.
LernzielParticipants are informed about recent and ongoing research in the field. Presenting doctoral students obtain feedback on their dissertation research plan.
InhaltThe covers the broadly understood field of behavioral science, including theoretical as well as empirical research 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.
Voraussetzungen / BesonderesDoctoral students in D-GESS can obtain 2 credits for presenting their dissertation research plan.
851-0252-15LNetwork Analysis
Particularly suitable for students of D-INFK, D-MATH
3 KP2VU. Brandes
KurzbeschreibungNetwork 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.
LernzielStudents 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.
InhaltThe 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
SkriptLecture notes are distributed via the associated course moodle.
Literatur* 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.
851-0586-03LApplied Network Science: Social Media Networks Belegung eingeschränkt - Details anzeigen
Number of participant limited to 20
3 KP2SU. Brandes
KurzbeschreibungWe study applications of network science methods, this semester in the domain of social media.
Topics are selected for diversity in research questions and techniques
with applications such as friendship on Facebook, re-tweeting on Twitter, or multi-channel networks on YouTube.
Student teams present results from the recent literature, possibly with replication, in a mini-conference.
LernzielNetwork science as a paradigm is entering domains from engineering to the humantities but application is tricky.
By examples from recent research on social media, 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.