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12 Jul
12. Jul. 2022 14. Jul. 2022


Purpose and Description

In this course, the foundations of (longitudinal) social network analysis will be covered. Partici-pants will learn how they can set up a (longitudinal) social network study: theoretical back-ground of social networks, research questions at different levels, data collection and ethical con-cerns, and understanding of the metrics.
The course learns participants to conceptualize and to set-up a social network study on their own. By practical assignments and in-depth discussions, the lecturer will support them in finding answers to the following questions: Why use social network analysis? What social network-re-search question to ask? How to get social network data? What are the options for analyzing so-cial network data? The main assignment in this course is to prepare a short proposal within a group and present it at the end of the course. This can be assessed with a pass or fail for the course participants who need the credits. Each of the participants will write their reflection on their learning process and how they will use the course material in the future.

Learning goals

After finishing the course, the students are expected to:
• be able to explain when and why social network analysis should be applied rather than conventional statistical techniques
• be able to formulate research questions at different levels (node, dyadic, and network level)
• be able to design a social network study which can be used for their (master thesis/ PhD) project
• have insight in the ethical concerns related to social network research, e.g., data collec-tion
• apply the content of the course to their own research project by asking critical questions and take part in discussions and assignments
• collaborate in small groups.  


July DatesTimesEvent or TopicAssignment



12.07.10:00-17:30Lecture 10.00-12.00
Seminar 12.00-17.00
Hand in assignment/ discuss progress in class: 17.00-17.30
Introduction to SNA
Theoretical background
Research questions
Get to know each other.
Discuss expectations and how you can collaborate.
Decide about the topic.
Topic proposal + preliminary research ques-tions. Define dependent and independent variables; node, dyadic, network-level variables.
Draft an outline with theoretical background, RQs, define DV and IV, levels.
13.07.10:00-17:30Lecture 10.00-12.00
Seminar 12.00-17.00
Hand in assignment/ discuss progress in class: 17.00-17.30  
Data collection
Ethical aspects
Metrics and analysis  
Prepare presentation including theoretical background, RQs, methods (ego networks/ sociocentric networks).
Create a document with two nomination questions and at least two attributes.  

Deadline 18:00!  
Lecture 10.00-12.00
Presentations: 12.00-15.00
Writing individual reflection 15.00-17.00/18.00  
Recap of the main topics + illustration of longitudinal SNA-research
Final presentations
Individual reflection  
Hand in the presentation
Hand in the individual reflection at 18.00  


The student will pass the course (if the student needs the credits):
- if the student actively participates during the course
- presented the proposal and handed in the group presentation on time
- handed in the individual reflection of 800-1000 words on time. In the individual reflection the following question will be addressed: What did you learn from the course and how will you use this knowledge in your personal and professional life? The reflection can be based on own experience and two peer-reviewed references.


Introduction to SNA
Borgatti, S. P., Mehra, A., Brass, D. J., & Labianca, G. (2009). Network analysis in the social sciences. Science, 323, 892–895.
Kadushin, C. (2004). Introduction to Social Network Theory. Chapter 2. Some Basic Network Concepts and Propositions. Boston, MA.
Sweet, T. M. (2016). Social network methods for the educational and psychological sciences. Educational Psychologist, 51(3–4), 381–394.

Ego networks
Längler, M., Brouwer, J., Timmermans, A., & Gruber, H. (2021). Exploring change in networks supporting the deliberate practice of popular musicians. Psychology of Music, 20210419.

Illustration longitudinal SNA
Brouwer, J., de Matos Fernandes, C. A., Steglich, C. E. G., Jansen, E. P. W. A., Hofman, W. H. A., Flache, A. (2022). The development of peer networks and academic performance in learning communities in higher education. Learning and Instruction, 80. Open access link:  


Dr. Jasperina Brouwer, Assistant Professor
Faculty of Behavioural and Social Sciences
University of Groningen  


Prof. Dr. Lysann Zander
Arbeitsbereich Empirische Bildungsforschung
Institut für Erziehungswissenschaft


12. Jul. 2022 14. Jul. 2022


Prof Dr. Lysann Zander
Institut für Erziehungswissenschaft
Schloßwender Str. 1
30159 Hannover