Tomáš Lintner, MA
Networks are everywhere. Whether we are aware of it or not, every day and every moment, we create, co-create, and re-create countless social networks. From our closest relationships with friends, family, classmates, and colleagues to interactions on social media; from syntactical links between words to trade between countries... We are all part of wider ecosystems and social network analysis (SNA) aims to grasp the interconnectedness of the world believing that our position within these ecosystems is as important as are our direct connections. SNA is a versatile approach to many real-world questions and therefore has found its place in a range of fields such as sociology, psychology, education, international relations, economy, neuroscience, linguistics, digital humanities, and media studies.
SNA gives researchers many new opportunities. Just to mention a few:
This summer school will equip you with fundamentals of SNA in humanities and social sciences and you will get your hands on Gephi software. At the end of the summer school, you will have performed your very own SNA project and you will present the results with stunning (and meaningful) network visualizations to your peers.
This summer school is for BA/MA students with no prior experience with SNA.
On 6 August, we will end the teaching part of the summer school. During the following weekend (7-8 August), you will be able to take the test, which will contain questions from theory of social networks we will have covered. You will be allowed to retake the test once. A minimum pass mark will be 70%.
During the teaching part (2-6 August), you will have already started thinking about your own SNA project and you will have started working at it. The SNA project will be a small-scale individual project employing SNA to address some question(s) from your own field of study. You will either collect data for the project yourself, use web mining, or use already collected data from a network data repository. After the teaching part, you will have over two days to prepare a short presentation (of approximately 10 minutes) on the topic of your research project. Ideally, you will already have some preliminary results and visualizations. On 9 August, all students will present their projects to others. You will get feedback both from your peers and from the instructors. Afterwards, you will have time until 23 August to write up your project and hand in a final report. The written report will be in the form of a short research article of approximately 3000 words. A minimum pass mark will be 70%. If you do not meet the threshold you will be allowed to resubmit.
The summer school will be intense, but it will be worth it :)
The summer school is divided into 3 blocks:
The teaching will take place during the week of 2-6 August and on 9 August 2021. Online classes will take place 08:00-12:00AM CET for four hours (two-double periods). The classes will be held via the communication platform ZOOM.
In this block, you will get familiar with basic theory, principles, and terms of social network analysis. We will address these questions:
In this block, you will get your hands on Gephi software and we will equip you will the necessary skills to perform your very own first social network analysis. We will address these questions:
In this block, you will present your own SNA project to your peers. We will together discuss your ideas, preliminary results, and visualizations.
At the end of the Block 3, you will have acquired key SNA ideas, you will have a clear picture on how to perform SNA in your own settings, and you will be ready to write up your project!
Tomáš is a PhD student and a junior research fellow at the Department of Educational Sciences. He employs social network analysis to study interaction, communication, and relationships in educational settings. He is a holder of IGA MU research grant “Studying Student Communication During Synchronous Online University Teaching with Social Network Analysis” and an author of a Czech methodological article on SNA in educational research – “Networks in education: Making use of social network analysis in educational research”. Tomáš loves learning as much as he does teaching, so he regularly participates in seminars and workshops focused on advanced quantitative methods. Before joining the Department, he studied MA in Education at UCL Institute of Education.
Libor is an assistant professor at the Department of Educational Sciences. His research interest lies primarily in the e-learning and digital technologies in education, with a focus on learning analytics and educational data mining. Libor has experience with collaboration on several research projects supported by the Czech Science Foundation and has published in prestigious international as well as Czech journals. He was awarded by the Czech Educational Research Association for a remarkable research-oriented publication employing social network analysis in an educational context (“Social Networks of Authors Publishing in Educational Sciences Between 2009 and 2013: An Exploratory Analysis”).
B2 English, high-school math, and active BA/MA studies in humanities or social sciences. You do not need to have any experience with social network analysis or Gephi.
Please follow this link and choose the correct programme. Do not forget to include all the necessary information (and documents if requested) including writing a short statement of purpose. We will contact you afterwards to tell you if your application was successful and to discuss the further steps (including the deposit payment) with you.