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Regular version of the site
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Network Sciences: fundamental network research and analytical decision support for government and business

Priority areas of development: sociology, humanitarian
2020

Publications:


Zaytsev D., Galina A., Sokol A. Cross-National Comparison of Protest Publics’ Roles as Drivers of Change: From Clusters to Models, in: Protest Publics. Toward a New Concept of Mass Civic Action. Switzerland : Springer, 2019. С. 157-182. 
Shmaltsev N. I., Zaytsev D. Protesters as the “Challengers of the Status Quo” in Embedded Democracies: The Cases of Iceland, the United Kingdom, and the United States, in: Protest Publics. Toward a New Concept of Mass Civic Action. Switzerland : Springer, 2019. С. 183-201. 
Zaytsev D., Kuskova V. Data Envelopment Analysis as a Tool to Evaluate Marketing Policy Reliability, in: Reliability and Statistical Computing.: Springer, 2020. С. 289-304. 
Batagelj V., Ferligoj A., Doreian P. Bibliometric analyses of the network clustering literature, in: Advances in Network Clustering and Blockmodeling.: Wiley, 2020. С. 11-64. 
Batagelj V. Clustering approaches to networks, in: Advances in Network Clustering and Blockmodeling.: Wiley, 2020. С. 65-104. 
Batagelj V. Corrected overlap weight and clustering coefficient., in: Challenges in Social Network Research - Methods and Applications.: Springer, 2020. С. 1-16. 
Ferligoj A., Batagelj V., Doreian P. Conclusions and Directions for Future Work, in: Advances in Network Clustering and Blockmodeling.: Wiley, 2020. С. 389-397. 
Cugmas M., Ferligoj A., Kronegger L. Scientific co-authorship networks, in: Advances in Network Clustering and Blockmodeling.: Wiley, 2020. С. 363-387. 
ŽNIDARŠIČ A., Doreian P., Ferligoj A. Treating missing network data before partitioning, in: Advances in Network Clustering and Blockmodeling.: Wiley, 2020. С. 189-224. 
Batagelj V., Kejzar N., Korenjak–Cerne S. Clustering of modal-valued symbolic data // Advances in Data Analysis and Classification. 2020. P. - . doi
Batagelj V. On Fractional Approach to Analysis of Linked Networks // Scientometrics. 2020. Vol. 123. P. 621-633. doi
Batagelj V., Maltseva D. Temporal Bibliographic Networks // Journal of Informetrics. 2020. Vol. 14. No. 1. P. 1-14. doi
Булычева Е. Е., Мальцева Д. В. Выделение актуальных тематик в социологии: взгляд сквозь призму анализа сети цитирований // Мониторинг общественного мнения: Экономические и социальные перемены. 2020. № 6. C. 113-140. doi
Зангиева И. К., Лесных К. А. Межгрупповые различия в установках к людям с расстрой­ствами аутистического спектра (РАС) // Мониторинг общественного мнения: Экономические и социальные перемены. 2020. № 5. C. 559-577. doi
Oldring A., Milekhina A., Brand A. Tweeting Tsunami: Influence and Early Warning in British Columbia // Canadian Journal of Communication. 2020. Vol. 45. No. 3. P. 387-409. doi
Ferligoj A., Cugmas M., Kogovšek T., Batagelj Z. The social support networks of elderly people in Slovenia during the Covid-19 pandemic // PLoS ONE. 2020. 
Korenjak–Cerne S., Kejzar N., Batagelj V. Clustering and Generalized ANOVA for Symbolic Data Constructed from Open Data, in: Advances in Data Sciences: Symbolic, Complex and Network Data.: ISTE, Wiley, 2020. С. 209-228. 
Gradoselskaya G., Karpov I., Shcheglova T. Mapping of politically active groups on social networks of Russian regions (on the example of Karachay-Cherkessia Republic), in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics.: Springer, 2020. С. 187-200. 
Zaytsev D., Kuskova V., Lushnikova P., Khvatsky G. Cross-efficiency of International Sanctions: Application of Data Envelopment Analysis and Network Methodology, in: Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Kazan, Russia, July 17–19, 2019, Revised Selected Papers. Communications in Computer and Information Science.: Springer, 2020. С. 72-82. 
Zaytsev D., Gregory K., 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. С. 231-244. 
Shcheglova T., Gradoselskaya G., Karpov I. Methodology for measuring polarization of political discourse: case of comparing oppositional and patriotic discourse in online social networks, in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics.: Springer, 2020. С. 219-230.