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  • Measurement of social processes in political sciences, business and society in general with the use of network analysis instruments

Measurement of social processes in political sciences, business and society in general with the use of network analysis instruments

Priority areas of development: sociology
2019
The project has been carried out as part of the HSE Program of Fundamental Studies.

Goal of research

Implementation of applied and fundamental research using network analysis in the field of social sciences using traditional developments and new tools, models and methods developed in other scientific areas.

Methodology

Mathematical methods of social network analysis, which due to the goals and objectives of a particular project may involve studying ego, complete, temporal, spatial, weighted, or multi–relational networks.

Empirical base of research

Data collected by the Laboratory members in their disciplinary areas – secondary data obtained from publicly available sources or scraped from web sites with laboratory’s proprietary scripts (statistics, bibliographical data, data from social networking sites), and primary data collected through mass surveys. Each research project has its own (in some cases unique) information base.

Results of research

The studies conducted by the International Laboratory`s representatives are oriented to practical application. Simultaneously, the Lab holds a number of projects in different disciplinary areas (sociology, political science, management, etc.) and thematically unrelated to each other, but unified by the implementation of common methodology of social network analysis (including its new methods developed in the Lab). In this regard, the project has resulted in the number of independent projects at different stages of implementation, with some being continued from 2018 and some being initiated in 2019.

As before, in 2019 the work on methodological developments was carried out within certain disciplinary areas. According to their research subjects, the projects can be divided into the following groups:

  • Sociology of science: the study of scientific disciplines through the quantitative analyses based on methods and algorithms developed in scientometrics, bibliometric, and informetrics,

  • Sociology of media and mass communications: the study of the information dissemination and behavior of individuals in the online environments,

  • Political science: the study of political processes using statistical methods,

  • Management and organizational studies: the study of networks in management, formal and informal groups and collectives.

In addition to tasks motivated by the subject, the projects were aimed to solving a number of methodological problems related to the construction and development of new tools, models and methods of network analysis, as well as their application and testing on various databases through the implementation of applied research.

Each project has its own research methodology, depending on the discipline. At the same time, all Laboratory projects have in common the application of a social network analysis, which, depending on the goals and objectives of a specific project, may involve the study of ego-networks or complete network structures, dynamic (temporal), spatial, signed, or multilevel networks.

The results of the project are already published in indexed international journals on social network analysis, social sciences, and computer sciences. Some articles are going to be published in 2020. According to the results of the International Summer School and special sections at EUSN and ARS conferences devoted to the analysis of networks in science, an agreement was reached on the preparation of a special issue on this topic in the “Network Science” journal (one of the key journals in the field of network analysis). Regular discussions of the projects were held during the Lab`s weekly seminars. Results of research projects were presented to an academic and business community at the conferences (including those organized with the Laboratory) abroad and in Russia. Results of the studies can be used by a number of researchers using network methodology and working in close disciplinary areas (sociology, political sciences, management, and computer science).

Level of implementation, recommendations on implementation or outcomes of the implementation of the results

The level of implementation varies among projects according to their goals. Completed projects may be implemented immediately in the spheres of sociology, political science, management and computer science as their results are published in respective outlets. 

Publications:


Градосельская Г. В., Щеглова Т. Е., Карпов И. А. Картирование политически активных групп в Фейсбуке: динамика 2013-2018 гг. // Вопросы кибербезопасности. 2019. Т. 4. № 32. С. 94-104. doi
Gradoselskaya G., Shcheglova T. Theoretical Foundation of Information Waves Investigation in Social Networks, in: 2019 Twelfth International Conference "Management of large-scale system development" (MLSD). M. : IEEE, 2019. P. 1-3. doi
Градосельская Г. В., Щеглова Т. Е. Теоретические основы исследования информационных волн в социальных сетях // В кн.: УПРАВЛЕНИЕ РАЗВИТИЕМ КРУПНОМАСШТАБНЫХ СИСТЕМ MLSD'2019 / Под общ. ред.: С. Н. Васильев, А. Цвиркун. ИПУ РАН, 2019. С. 1196-1199.
Zaytsev D. G., 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. G., 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
Zaytsev D. G., Kuskova V., Lushnikova P., Khvatsky Gregory. 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 Vol. 1086. Springer, 2020. doi
Batagelj V., Maltseva D. V. Temporal Bibliographic Networks // Journal of Informetrics. 2020. Vol. 14. No. 1. P. 1-14. doi
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. P. 209-228.
Advances in Network Clustering and Blockmodeling / Ed. by P. Doreian, V. Batagelj, A. Ferligoj. Wiley Series in Computational and Quantitative Social Science. Wiley, 2020.
Batagelj V. Corrected overlap weight and clustering coefficient., in: Challenges in Social Network Research - Methods and Applications. Springer, 2020. doi Ch. . P. 1-16. doi
Zaytsev D. G., Kuskova V. Efficient Marketing Strategy: Application of Data Envelopment Analysis as an Optimization Tool, in: Proceedings - 25th ISSAT International Conference on Reliability and Quality in Design 2019. , 2019. P. 228-232.
Grinkevich Y., Kuskova V., Shabanova M. Professional development programmes – why do universities need them? A case study from Russia // Perspectives: Policy and Practice in Higher Education. 2019. P.  - . doi
Kuskova V., Zaytsev D. G. Clustering Based on Data Envelopment Analysis: Application to Management Research and Practice, in: Proceedings - 25th ISSAT International Conference on Reliability and Quality in Design 2019. , 2019. P. 142-145.
Cugmas M., DeLay D., Žiberna A., Ferligoj A. Symmetric core-cohesive blockmodel in preschool children’s interaction networks // Plos One. 2019
Batagelj V. On Fractional Approach to Analysis of Linked Networks // Scientometrics. 2020
Kuskova V., Khvatsky Gregory, Zaytsev D. G., 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.
Batagelj V. Clustering approaches to networks, in: Advances in Network Clustering and Blockmodeling / Ed. by P. Doreian, V. Batagelj, A. Ferligoj. Wiley Series in Computational and Quantitative Social Science. Wiley, 2020. Ch. 3. P. 65-104.
ŽNIDARŠIČ A., Doreian P., Ferligoj A. Treating missing network data before partitioning, in: Advances in Network Clustering and Blockmodeling / Ed. by P. Doreian, V. Batagelj, A. Ferligoj. Wiley Series in Computational and Quantitative Social Science. Wiley, 2020. Ch. 7. P. 189-224.
Cugmas M., Ferligoj A., Kronegger L. Scientific co-authorship networks, in: Advances in Network Clustering and Blockmodeling / Ed. by P. Doreian, V. Batagelj, A. Ferligoj. Wiley Series in Computational and Quantitative Social Science. Wiley, 2020. Ch. 13. P. 363-388.
Batagelj V., Ferligoj A., Doreian P. Bibliometric analyses of the network clustering literature, in: Advances in Network Clustering and Blockmodeling / Ed. by P. Doreian, V. Batagelj, A. Ferligoj. Wiley Series in Computational and Quantitative Social Science. Wiley, 2020. Ch. 2. P. 11-63.
Mali F., Pustovrh T., Marjan C., Ferligoj A. The personal factors in scientific collaboration: views held by slovenian researchers // Corvinus Journal of Sociology and Social Policy. 2018. No. 10. P. 3-24. doi
Моисеев С. П. Грушинский концепт "масса" в новую эпоху: сеть, рой, множество и племя // В кн.: Открывая Грушина Т. 5. М. : Факультет журналистики МГУ имени М.В. Ломоносова, 2019. С. 199-214.
Oldring A., Brand A. 1 Tweeting Tsunami: Influence and Early Warning in British Columbia // Canadian Journal of Communication. 2019
Kuskova V., Zaytsev D. G., Khvatskiy G., Lushnikova P. 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 Vol. 1086. Springer, 2020. doi
Maltseva D. V., Zurc J., Moiseev S. Mixed methods research: the development of the field // Journal of Mixed Methods Research. 2019
Maltseva D. V., Batagelj V. X-metrics: the development of the fields of bibliometrics, scientometrics, informetrics, and others // Scientometrics. 2019
Žnidaršxc A., Bagga A., Brezavšcek A., Maltseva D. V. The analysis of keywords in the field of green information systems and green information technology // Network Science. 2019
Inshakov I., Maltseva D. V. Biopolitics: Studying the Development of the Field Using SNA // Foucault Studies. 2019
Булычева Е. Е., Мальцева Д. В. История социологии: Взгляд на развитие дисциплины сквозь призму анализа сети цитирований // Социологические исследования. 2019
Cugmas M., Žiberna A., Ferligoj A. Mechanisms generating asymmetric core-cohesive blockmodels // Metodoloski Zvezki. 2019. Vol. 16. No. 1. P. 17-41.
Zaytsev D. G., 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 / Отв. ред.: N. Y. Belyaeva, D. G. Zaytsev, V. A. Albert. Switzerland : Springer, 2019. doi P. 157-182. doi