Ulrik Brandes: Catalogue data in Spring Semester 2021
|Name||Prof. Dr. Ulrik Brandes|
|Name variants||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||0 credits||2K||D. Helbing, U. Brandes, C. Hölscher, M. Kapur, 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.
|Literature||Will be provided on request.|
|Prerequisites / Notice||Doctoral students in D-GESS can obtain 2 credit points for presenting their dissertation research plan.|
|851-0252-06L||Introduction to Social Networks: Theory, Methods and Applications|
This course is intended for students interested in data analysis and with basic knowledge of inferential statistics.
|3 credits||2G||C. Stadtfeld, U. Brandes|
|Abstract||Humans are connected by various social relations. When aggregated, we speak of social networks. This course discusses how social networks are structured, how they change over time and how they affect the individuals that they connect. It integrates social theory with practical knowledge of cutting-edge statistical methods and applications from a number of scientific disciplines.|
|Objective||The aim is to enable students to contribute to social networks research and to be discriminating consumers of modern literature on social networks. Students will acquire a thorough understanding of social networks theory (1), practical skills in cutting-edge statistical methods (2) and their applications in a number of scientific fields (3). |
In particular, at the end of the course students will
- Know the fundamental theories in social networks research (1)
- Understand core concepts of social networks and their relevance in different contexts (1, 3)
- Be able to describe and visualize networks data in the R environment (2)
- Understand differences regarding analysis and collection of network data and other type of survey data (2)
- Know state-of-the-art inferential statistical methods and how they are used in R (2)
- Be familiar with the core empirical studies in social networks research (2, 3)
- Know how network methods can be employed in a variety of scientific disciplines (3)
|851-0254-00L||Network Science Project|
Does not take place this semester.
It is advisable to take at least one of 851-0252-06 Introduction to Social Networks, 851-0252-15 Network Analysis, or 851-0252-13 Network Modeling beforehand.
Proficiency in programming and data analysis are helpful but can be compensated for by a firm understanding of the foundations relevant for the particular study.
|3 credits||2P||U. Brandes, C. Stadtfeld|
|Abstract||Study project involving network data in a selected field.|
|Objective||Practical experience with, and a contextual understanding of, the links between a research question, domain-specific theory, and computational methods in network science.|
|Content||Individually or in small groups, students carry out a project in which an original research question is addressed using network data. While network approaches are increasingly common in domains from archaeology and digital media to transportation and zoology, applications are often driven by the availability of (found, observational) data.|
Special emphasis is therefore placed on the consideration of domain-specific theory and the possibility to adapt data collection and mathematical methods accordingly. Studies may vary by domain of interest and the relative importance of theory, data, methods, implementation issues, and other aspects. In particular, the focus may be on data collection instruments or theory-inspired method development and implementation.
|Prerequisites / Notice||Project topics will be introduced during an initial meeting on Friday, March 5, 16:15-17:45, in WEP J 11. Subsequent meetings with the respective project teams will be by appointment.|
|851-0586-02L||The Spectacles of Measurement||3 credits||2V||U. Brandes|
|Abstract||If you can't measure it, you can't manage it. Explorations into mathematical foundations and societal implications of measuring humans, processes, and things in an increasingly datafied world.|
|Objective||Students have a basic understanding of what makes a property quantifiable. They know the difference between operational and representational measurement, and the consequences this has for both, the collection of data and its use in decision making and control. With a critical attitude toward datafication, contextual differences are appreciated across domains such as science and engineering, business and entertainment, health and sports, governance and policy making.|
- scales and meaningfulness
- direct vs. indirect
- conjoint measurement
- units and standards
- sensors and instruments
- items and questionnaires
- indices and datafication
- administration and coordination
- discrimination and behavior
- smart living
|Lecture notes||Slides made available in a course moodle.|
|Prerequisites / Notice||Students pair up in teams to write an essay on a measurement problem they care about (such as one pertinent to their discipline or research). The essay is pitched to the others in the course during a poster session at the end of the semester (may have to be replaced with an online session in FS21).|
|851-0586-03L||Applied Network Science: Sports Networks |
Number of participant limited to 20
|3 credits||2S||U. Brandes|
|Abstract||We study applications of network science methods, this time in the domain of sports.|
Topics are selected for diversity in research questions and techniques
with applications such as passing networks, team rankings, and career trajectories.
Student teams present results from the recent literature, possibly with replication, in a mini-conference shortly before the start of EURO 2020 [sic].
|Objective||Network science as a paradigm is entering domains from engineering to the humantities but application is tricky.|
By examples from recent research on sports, sports administration, and the sociology of sports, 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.
|Literature||Original research articles will be introduced in the first session. General introduction:|
Wäsche, Dickson, Woll & Brandes (2017). Social Network Analysis in Sport Research: An Emerging Paradigm. European Journal for Sport and Society 14(2):138-165. DOI: 10.1080/16138171.2017.1318198