CGES runs ‘St. Petersburg Summer School on Network Analysis’ for Russian and international graduates, and early-career social scientists and culture scholars every two years since 2015. The school is associated with the CGES research area ‘Network Structures in Germany, Europe and Russia’.
Over the last decade, the interest to network analysis has increased dramatically. Although the approach rapidly expands and draws attention of Russian academics, it is still at an early stage of development and lacks both local experts and systematic training programmes. In order to fill in this gap, the school brings internationally recognized experts to introduce early-career researchers excited about but unfamiliar with social network analysis to its basic methods, tools, and techniques. Providing local researchers engaged in social and cultural studies with affordable high-quality training in network analysis, the School has no analogues in Russia, hence attracting students, researchers, and teachers from all over the country. Moreover, unlike other network analysis schools worldwide, the St. Petersburg school specifically targets researchers with little or none background in mathematics and statistics, and simultaneously, uniquely blends network-analytical foci relevant to socio-cultural scholars, such as socio-semantic network analysis, multi-level network analysis, and mixed-method network analysis. As a result, the School attracts not only students but also experienced researchers, and not only from Russia, but from all over the world.
The School’s programme consists mainly of introductory courses and workshops related to data collection and analysis, including usage of the corresponding software. Participants also present and discuss their own projects with each other and with the invited experts in order to get feedback and recommendations on how to apply network analysis in their research.
Furthermore, participants have an opportunity to join the workshop on publishing in ‘Social Networks’ - the main academic journal on network analysis and one of the highest-rank sociology outlets worldwide. This workshop is focused on the kinds of work preferred by the journal, the requirements to the manuscripts’ content, the viable strategies of paper positioning, and the nuances of working with editors and reviewers. The workshop is conducted by researchers experienced with the journal.
Prior knowledge of network analysis, programming, or mathematical statistics is not mandatory to participate in the School. Meanwhile, a well-argumented motivation to learn network analysis and a relevant project description are regarded as the key selection criteria.
The first School took place in Saint-Petersburg in 2015 and lasted for eight days. 20 BA, MA, and PhD students – about half of all applicants – from leading Russian universities, such as St. Petersburg State University, National Research University – Higher School of Economics, European University at St. Petersburg, Moscow State University, and ITMO University, attended six courses devoted to basic concepts and methods of network analysis applied to social, cultural, and technical dimensions of European urban landscapes.
The School was opened by Andres Cardona, Bielefeld University who provided an introduction to the main notions and approaches of network analysis. It was followed by a workshop by Beate Volker, University of Amsterdam ‘Analyzing European urban communities: Key 
tools and techniques’. Johan Koskinen, University of Manchester introduced participants to modeling of the dynamics of spatially embedded social networks with Exponential Random Graph Models. The second-to-last day of the Summer School was devoted to network analysis of urban groups and communities using semantic and socio-semantic techniques, delivered by Jana Diesner, University of Illinois at Urbana Champaign. The School was finished by Camille Roth, National Center for Scientific Research of France, who gave a workshop on the analysis of European urban mobility networks. In a concluding session, participants, teachers, and organizers discussed the results of their work during the six days as well as more general problems and perspectives of network analysis of urban landscapes.
Find the programme of the 2015 Summer School here.
On July 10-16, 2017, the Second School introduced students and junior researchers to the basics of social, semantic, and socio-semantic network analyses. 20 students and early-career researchers from Russia, Czech Republic, Slovakia, Spain, Hungary, UK, and Sweden, selected out of 53 applicants, attended six days of classes divided into two courses by experts from some of the leading European universities.
During the first three-day course, Adina Nerghes, VU University Amsterdam and Ju-Sung Lee, Erasmus University Rotterdam provided an introduction to the main concepts and methods of social network analysis and semantic network analysis. Participants learned how to use the ORA-NetScenes network analysis package for producing reports on key entities, node-level measures, graph-level measures, and AutoMap for cleaning and preprocessing raw text data. Within the workshop by Johan Koskinen, University of Manchester students were introduced to Exponential Random Graph Models. Participants explored different possibilities of network modelling while working with various specific pieces of software, such as the ’network’, ’sna’, and ’statnet’ packages in R and MPNet.
The programme of the 2017 Summer School can be found here.
The third Summer School, July 8-13, 2019, was devoted to state-of-the-art techniques of network analysis based on European social and cultural network data. The School attracted over 60 applications by students and teachers from Russia, Germany, Great Britain, Norway, Poland, the Czech Republic, Brazil, Malaysia, and other countries. Owing to the large number of applications, the acceptance rate was about 25%.
Within the School, Elisa Bellotti, Mitchell Centre for Social Network Analysis, University of Manchester held a two-day workshop on ‘Introduction to network analysis and mixed methods of network data collection’. Julia Brennecke, University of Liverpool Management School conducted a two-day course ‘Introduction to Exponential Random Graph Models for Network Analysis’, designed to familiarize participants with the principles behind ERGMs and to gain hands-on experience with German and European datasets using specialized software.
See the programme of the 2019 Summer School here.
Participation in the School stimulates social ties between the participants and motivates graduates and early-career researchers to find out more about various opportunities provided by the CGES in terms of research mobility, international scientific dialogue, the MA Programme ‘European Societies’, and CGES PhD Fellowship Programme. Moreover, the participants of the Schools often develop strong ties with the CGES and expand cooperation with the Centre. For instance, in January and in May 2018, Sebastian Stevens, a participant of the 2017 School and a PhD candidate at the University of Plymouth, UK conducted several research internships at the CGES in St. Petersburg University. Today, he is an affiliated researcher of the CGES, collaborating with other CGES researchers and teachers, which opened opportunities for scientific and exchange cooperations between the CGES and the University of Plymouth.
At the end of 2017, a participant of the second Summer School, Irina Antoschyuk, St Petersburg State University and European University at St. Petersburg received a travel grant from the CGES and visited several universities and Cambridge Science Park, met Russian-speaking scientists and collected data for her project on diaspora knowledge networks of Russian-speaking computer scientists. Irina also won the CGES Russian-European research papers competition twice, and is a regular participant of the ‘Networks in the Global World’ conference organized by the CGES.
The participants of the Summer School find the knowledge they gain valuable for their future research career development. For example, Olga Silyutina, Sociology department at NRU ‘Higher School of Economics’, participant of the Summer School in 2017, tells: “St. Petersburg Summer School on Network Analysis featured a large amount of useful information, practice, and interaction with experts and other participants. Being a student of the School, I gained experience of working with word processing programmes, downloading of internet data, constructing semantic and social networks, and improved my R programming language skills. This experience contributed to the emergence of new research issues and ideas. I find the knowledge gained very useful and hope to apply it in my future research.”