ANR-Lab at NetGlow`2018 in St.Petersburg
Members of the International laboratory for Applied Network Research took part at the Conference “Networks in the Global World. Principles behind Structures: Patterns of complexity in European societies and beyond”, which was held on July 4-6 in St. Petersburg.
ANR-Lab members Daria Maltseva, Stanislav Moiseev jointly with Anna Shirokanova (Laboratory for Comparative Research, NRU HSE) organized a session “Mixed methods in Social network analysis”. On the session, different issues on the integration of quantitative and qualitative approaches in network analysis, such as mixed methods research designs, techniques for data collection and extraction, software development, methodological approaches to interpretation, applied analyses of mixed data, and their theoretical foundation were discussed. In two days there were 8 reporst presented at the session, including the following done the organizers and other members of the Laboratory:
· Daria Maltseva and Anna Shirokanova - Mixed methods in social network analysis: combining quantitative and qualitative approaches
· Daria Maltseva and Stanislav Moiseev - Building networks from biographical texts: different approaches to data extraction
· Stanislav Moiseev, Daria Maltseva, Anna Shirokanova - Networks of collaboration and interaction between Russian sociologists: from biographical interviews to network analysis
· Dmitry Zaytsev and Iliya Karpov - Civil participation in Russia: from non-conventional to conventional forms (case of municipal elections in Moscow)
Galina Gradoselskaya, Ilia Karpov, and Tamara Scheglova presented the report “Mapping of politically active groups on social networks of Russian regions (on the example of Karachay-Cherkess Republic)” at the session “Network Analysis of Political and Policy-Making Domains”.
The abstracts of all presentations can be found by the .
Besides, Daria Maltseva and Vladimir Batagelj conducted a 4-hrs. workshop on the topic “Analysis of Bibliographic Networks”, where they told about the bibliographic data and errors that can be encountered when they are collected and processed, and provided a way to build networks based on such data and analyze them.