Computational Social Sciences

In the modern world, social phenomena tend to be incredibly complex and extremely difficult to study using tool of classical data analysis. This project is focused on applying modern data analysis tools and methods to problems in social sciences. These methods allow us to study social processes without unnecessary simplification.

So far, we have successfully applied this approach to the fields of policy and innovation studies. However, there still many questions left unanswered and theories untested. How are events represented in new and old media? Do experts have influence over policies in countries around the world? How do people form groups in the always-online world?

The main goal of this project is the development and testing of a cohesive theoretico-methodological framework that will enable social scientists of all backgrounds to use modern methods of data analysis in their studies.

Publications:

Zaytsev D., Gregory Khvatsky, Talovsky N., Kuskova V. Network Analysis Methodology of Policy Actors Identification and Power Evaluation (the case of the Unified State Exam introduction in Russia), in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics. Springer, 2020. doi

Kuskova V., Khvatsky Gregory, Zaytsev D., Talovsky N. Multilevel exponential random graph models application to civil participation studies Exponential Random Graph Models), in:  Proceedings of Analysis of Images, Social Networks and Texts – 9th International Conference, AIST 2019, Kazan, Russia, July 17-19, 2019, Revised Selected Papers. Lecture Notes in Computer Science. Springer, 2019

Zaytsev D., Talovsky N., Kuskova V., Khvatsky Gregory. The Entity Name Identification in Classification Algorithm: Testing the Advocacy Coalition Framework by Document Analysis (The Case of Russian Civil Society Policy), in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers  / Ed. by W. M. van der Aalst, V. Batagelj, D. I. Ignatov, M. Y. Khachay, V. Kuskova, A. Kutuzov, S. Kuznetsov, I. A. Lomazova, N. Loukachevitch, A. Napoli, P. M. Pardalos, M. Pelillo, A. Savchenko, E. Tutubalina. Vol. 11832. Cham : Springer, 2019. doi P. 276-288. doi

Zaytsev D., Drozdova D. Mapping Paradigms of Social Sciences: Application of Network Analysis, in: Computational Aspects and Applications in Large-Scale Networks. Springer Proceedings in Mathematics & Statistics Vol. 247. Springer, 2018. doi P. 235-253. doi

Associations and conferences: