politscienceПолитическая наукаPolitical science1998-1775ИНИОН РАН10.31249/poln/2021.04.05politscience-796Research ArticleИДЕИ И ПРАКТИКАДиффузионные сети: динамические аспекты сетевой теории и практикиDiffusion networks: dynamic aspects of network theory and practiceПодшибякинаТ. А.PodshibyakinaT. A.

Подшибякина Татьяна Александровна, кандидат политических наук, доцент, доцент кафедры теоретической и прикладной политологии Института философии и социально-политических наук

Ростов-на-Дону

Rostov-on-Don

tan5@bk.ruЮжный федеральный университетРоссияSouthern federal universityRussian Federation20211805202304Политические сети117134Copyright © Подшибякина Т.А., 20232023Подшибякина Т.А.Podshibyakina T.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.politnauka.ru/jour/article/view/796

Сравнительный анализ выявил недостаточную репрезентацию теорий сетевой динамики по сравнению с теориями сетевой статики, исключение составляют «стратегическая реляционная теория сетевой динамики» К. Хэй и Д. Ричардса, акторно-сетевая теория Б. Латура и теория стохастических процессов, на основе которой строится большинство моделей сетевой динамики. В публикациях диффузионное направление, описывающее соответствующий вид сетей, менее представлено по сравнению с реляционистским и стохастическим подходами. Объектом данного исследования являются диффузионные сети, рассматриваемые как коммуникативный элемент процесса диффузии политики, т.е. канал распространения политики от одного субъекта к другому. Предметом изучения выступают политические практики когнитивного контроля в диффузионных сетях. Методологическим основанием стала концепция динамики диффузионных сетей, позволяющая описать эффекты «когнитивных ограничений», возникающие в сети Интернет. В развитие данной темы предполагается продолжить исследование выявления технологий когнитивного контроля в диффузионных сетях, построенных на манипулировании когнитивными способностями участников сетевых отношений. Эмпирическая часть исследования направлена на апробацию теоретических положений концепции динамики диффузионных сетей на примере практик сетевого контроля в виде политической когнитивной цензуры в ходе проведения диджитал-кампаний. Для обоснования выводов используется анализ big data, осуществленный методом мониторинга сетевого онлайн-пространства при помощи ресурсов систем «Медиалогия» и YouScan. Результатом стала концептуализация понятия «когнитивного сетевого контроля» применительно к диффузионным сетям, описание основного динамического индикатора - скорости распространения политической информации в сетевых сообществах и выявление технологий когнитивного стратегического воздействия в диджитал-практиках.

Comparative analysis revealed insufficient representation of the theories of network dynamics in comparison with the theories of network statics, with the exception of the “strategic relational theory of network dynamics” by K. Hay and D. Richards, the actor-network theory of B. Latour and the theory of stochastic processes, on the basis of which most models of network dynamics are built. In comparison with the relational and stochastic approaches, the diffusion direction describing the corresponding type of networks is less represented in the publications. The object of this study is diffusion networks, considered as a communicative element of the process of policy diffusion, that is, a channel for policy dissemination from one policy subject to another. The subject of the study is the political practices of cognitive control in diffusion networks. The methodological basis was the concept of the dynamics of diffusion networks, which allows us to describe the effects of “cognitive limitations” that arise in the Internet. In the development of this topic, it is planned to continue the research in the direction of identifying technologies of cognitive control in diffusion networks based on the manipulation of the cognitive abilities of participants in network relations. The empirical part of the study is aimed at testing the theoretical provisions of the concept of the dynamics of diffusion networks on the example of the practices of network control in the form of political cognitive censorship in the course of digital campaigns. To substantiate the conclusions, we use the big data analysis carried out by monitoring the online network space using the resources of the “Medialogia” and “YouScan” systems. The result was the conceptualization of the concept of “cognitive network control” in relation to diffusion networks, the description of the main dynamic indicator - the speed of dissemination of political information in network communities, and the identification of technologies for cognitive strategic influence in digital practices.

политическая диффузиядиффузионные политические сетиновые медиакогнитивный сетевой контролькогнитивная политическая цензурадинамикаpolitical diffusiondiffusive political networksnew mediacognitive network controlcognitive political censorshipdynamicsСтатья подготовлена в рамках проекта, поддерживаемого грантом РФФИ 19–011–31284 «Стратегии когнитивной политической цензуры как эффект “новых медиа”: украинский кейс в сравнительной перспективе»The article was prepared as part of a project supported by a grant from the Rus- sian Foundation for Basic Research 19–011–31284 “Strategies of cognitive political censorship as an effect of “new media”: the Ukrainian case in comparative perspective”ReferencesBartels K., Turnbull N. Relational public administration: a synthesis and heuristic classification of relational approaches. Public management review. 2020, Vol. 22, N 9, P. 1324-1346. DOI: 10.1080/14719037.2019.1632921Bartels K., Turnbull N. Relational public administration: a synthesis and heuristic classification of relational approaches. Public management review. 2020, Vol. 22, N 9, P. 1324-1346. DOI: 10.1080/14719037.2019.1632921Boehmke F.J. Brockway M., Desmarais B.A., Harden J.J., LaCombe S., Linder F., Wallach H. SPID: A new database for inferring public policy innovativeness and diffusion networks. Policy studies journal. 2020, Vol. 48, N 2, P. 517-545. DOI: 10.1111/psj.12357Boehmke F.J. Brockway M., Desmarais B.A., Harden J.J., LaCombe S., Linder F., Wallach H. SPID: A new database for inferring public policy innovativeness and diffusion networks. Policy studies journal. 2020, Vol. 48, N 2, P. 517-545. DOI: 10.1111/psj.12357Bennett W.L., Segerberg A. The logic of connective action: digital media and the personalization of contentious politics. Information, communication & society. 2012, Vol. 15, N 5, P. 739-768. DOI: 10.1080/1369118X.2012.670661Bennett W.L., Segerberg A. The logic of connective action: digital media and the personalization of contentious politics. Information, communication & society. 2012, Vol. 15, N 5, P. 739-768. DOI: 10.1080/1369118X.2012.670661Bond R., Fariss C., Jones J., Kramer A., Marlow C., Settle J., Fowler J. A 61-million-person experiment in social influence and political mobilization. Nature. 2012, Vol. 489, P. 295-298. DOI: 10.1038/nature11421Bond R., Fariss C., Jones J., Kramer A., Marlow C., Settle J., Fowler J. A 61-million-person experiment in social influence and political mobilization. Nature. 2012, Vol. 489, P. 295-298. DOI: 10.1038/nature11421Borgatti S.P., Mehra A., Brass D.J., Labianca G. Network analysis in the social Sciences.Science. 2009, Vol. 323, N 5916, P. 892-895. DOI: 10.1126/science.1165821Borgatti S.P., Mehra A., Brass D.J., Labianca G. Network analysis in the social Sciences.Science. 2009, Vol. 323, N 5916, P. 892-895. DOI: 10.1126/science.1165821Boushey G. Punctuated equilibrium theory and the diffusion of innovations. Policy studies journal. 2012, Vol. 40, N 1, P. 127-146. DOI: 10.1111/j.1541-0072.2011.00437.xBoushey G. Punctuated equilibrium theory and the diffusion of innovations. Policy studies journal. 2012, Vol. 40, N 1, P. 127-146. DOI: 10.1111/j.1541-0072.2011.00437.xCannarella J., Spechler J.A. Epidemiological modeling of online social network dynamics. arXiv preprint arXiv:1401.4208. 2014. Mode of access: https://arxiv.org/abs/1401.4208 (accessed: 02.07.2021).Cannarella J., Spechler J.A. Epidemiological modeling of online social network dynamics. arXiv preprint arXiv:1401.4208. 2014. Mode of access: https://arxiv.org/abs/1401.4208 (accessed: 02.07.2021).Castells M. The rise of the network society. Oxford: Blackwell publishers, 1996, 656 p.Castells M. The rise of the network society. Oxford: Blackwell publishers, 1996, 656 p.Desmarais B.A., Harden J.J., Boehmke F.J. Persistent policy pathways: inferring diffusion networks in the American states. American political science review. 2015, Vol. 109, N 2, P. 392-406. DOI: 10.1017/s0003055415000040Desmarais B.A., Harden J.J., Boehmke F.J. Persistent policy pathways: inferring diffusion networks in the American states. American political science review. 2015, Vol. 109, N 2, P. 392-406. DOI: 10.1017/s0003055415000040Gilardi F., Shipan C.R., Wüst B. Policy diffusion: the issue-definition stage. University of Zurich and University of Michigan, 2018. Mode of access: https://fabriziogilardi.org/resources/papers/policy-diffusion-issue-definition.pdf (accessed: 28.07.2020).Gilardi F., Shipan C.R., Wüst B. Policy diffusion: the issue-definition stage. University of Zurich and University of Michigan, 2018. Mode of access: https://fabriziogilardi.org/resources/papers/policy-diffusion-issue-definition.pdf (accessed: 28.07.2020).Gilardi F., Shipan C.R., Wüest B. The diffusion of policy frames: evidence from a structural topic model. American political science association. Annual meeting, Philadelphia, 1 September 2016-4 September 2016. 2016. Mode of access: https://www.zora.uzh.ch/id/eprint/143864/(accessed: 28.08.2020).Gilardi F., Shipan C.R., Wüest B. The diffusion of policy frames: evidence from a structural topic model. American political science association. Annual meeting, Philadelphia, 1 September 2016-4 September 2016. 2016. Mode of access: https://www.zora.uzh.ch/id/eprint/143864/(accessed: 28.08.2020).Greenan C.C. Diffusion of innovations in dynamic networks. Journal of the Royal statistical society. Series A (statistics in society). 2015, Vol. 178, N 1, P. 147-166. DOI: 10.1111/rssa.12054Greenan C.C. Diffusion of innovations in dynamic networks. Journal of the Royal statistical society. Series A (statistics in society). 2015, Vol. 178, N 1, P. 147-166. DOI: 10.1111/rssa.12054Hay C., Richards D. The tangled web of Westminster and Whitehall: the discourse, strategy and practice of networking within the British core executive. Public administration. 2000, Vol. 78, N 1, P. 1-28. DOI: 10.1111/1467-9299.00190Hay C., Richards D. The tangled web of Westminster and Whitehall: the discourse, strategy and practice of networking within the British core executive. Public administration. 2000, Vol. 78, N 1, P. 1-28. DOI: 10.1111/1467-9299.00190Hodas N., Lerman K. The simple rules of social contagion. Scientific reports. 2014, Vol. 4, N 4343. DOI: 10.1038/srep04343Hodas N., Lerman K. The simple rules of social contagion. Scientific reports. 2014, Vol. 4, N 4343. DOI: 10.1038/srep04343Holland P.W., Leinhardt S. A dynamic model for social networks. Journal of mathematical sociology. 1977, Vol. 5, N 1, P. 5-20. DOI: 10.1080/0022250x.1977.9989862Holland P.W., Leinhardt S. A dynamic model for social networks. Journal of mathematical sociology. 1977, Vol. 5, N 1, P. 5-20. DOI: 10.1080/0022250x.1977.9989862Jack S.L. The role, use and activation of strong and weak network ties: a qualitative analysis. Journal of management studies. 2005, Vol. 42, N 6, P. 1233-1259. DOI: 10.1111/j.1467-6486.2005.00540.xJack S.L. The role, use and activation of strong and weak network ties: a qualitative analysis. Journal of management studies. 2005, Vol. 42, N 6, P. 1233-1259. DOI: 10.1111/j.1467-6486.2005.00540.xJiang C., Chen Y., Liu K.J.R. Evolutionary dynamics of information diffusion over social networks. IEEE transactions on signal processing. 2014, Vol. 62, N 17, P. 4573-4586. DOI: 10.1109/tsp.2014.2339799Jiang C., Chen Y., Liu K.J.R. Evolutionary dynamics of information diffusion over social networks. IEEE transactions on signal processing. 2014, Vol. 62, N 17, P. 4573-4586. DOI: 10.1109/tsp.2014.2339799Kim M., Newth D., Christen P. Modeling dynamics of diffusion across heterogeneous social networks: news diffusion in social media. Entropy. 2013, Vol. 15, N 10, P. 4215-4242. DOI: 10.3390/e15104215Kim M., Newth D., Christen P. Modeling dynamics of diffusion across heterogeneous social networks: news diffusion in social media. Entropy. 2013, Vol. 15, N 10, P. 4215-4242. DOI: 10.3390/e15104215Lane D.C. Should system dynamics be described as a ‘hard' or ‘deterministic' systems approach? Systems research and behavioral science: the official journal of the international federation for systems research. 2000, Vol. 17, N 1, P. 3-22. :1%3C3::aid-sres344%3E3.0.co;2-7. DOI: 10.1002/(sici)1099-1743(200001/02)17Lane D.C. Should system dynamics be described as a ‘hard' or ‘deterministic' systems approach? Systems research and behavioral science: the official journal of the international federation for systems research. 2000, Vol. 17, N 1, P. 3-22. :1%3C3::aid-sres344%3E3.0.co;2-7. DOI: 10.1002/(sici)1099-1743(200001/02)17Latour B. Reassembling the social: an introduction to actornetwork-theory. Clarendon lectures in management studies. New York: Oxford university press, 2005, 301 p.Latour B. Reassembling the social: an introduction to actornetwork-theory. Clarendon lectures in management studies. New York: Oxford university press, 2005, 301 p.Lerman K. Information is not a virus, and other consequences of human cognitive limits. Future Internet. 2016, Vol. 8, N 2, P. 21. DOI: 10.3390/fi8020021 EDN: YDPAEMLerman K. Information is not a virus, and other consequences of human cognitive limits. Future Internet. 2016, Vol. 8, N 2, P. 21. DOI: 10.3390/fi8020021 EDN: YDPAEMLuo S., Du Y., Liu P., Xuan Z., Wang Y. A study on coevolutionary dynamics of knowledge diffusion and social network structure. Expert systems with applications. 2015, Vol. 42, N 7, P. 3619-3633. DOI: 10.1016/j.eswa.2014.12.038Luo S., Du Y., Liu P., Xuan Z., Wang Y. A study on coevolutionary dynamics of knowledge diffusion and social network structure. Expert systems with applications. 2015, Vol. 42, N 7, P. 3619-3633. DOI: 10.1016/j.eswa.2014.12.038Lupeng Z., Chen W. How do innovation network structures affect knowledge sharing? A simulation analysis of complex networks. Complexity. 2021, Vol. 21, P. 17. DOI: 10.1155/2021/5107630Lupeng Z., Chen W. How do innovation network structures affect knowledge sharing? A simulation analysis of complex networks. Complexity. 2021, Vol. 21, P. 17. DOI: 10.1155/2021/5107630Maggetti M. The rewards of cooperation: the effects of membership in European regulatory networks. European journal of political research. 2014, Vol. 53, N 3, P. 480-499. DOI: 10.1111/1475-6765.12042Maggetti M. The rewards of cooperation: the effects of membership in European regulatory networks. European journal of political research. 2014, Vol. 53, N 3, P. 480-499. DOI: 10.1111/1475-6765.12042Netelenbos B. Bringing back Max Weber into network governance research. Critical policy studies. 2020, Vol. 14, N 1, P. 67-85. DOI: 10.1080/19460171.2018.1523738Netelenbos B. Bringing back Max Weber into network governance research. Critical policy studies. 2020, Vol. 14, N 1, P. 67-85. DOI: 10.1080/19460171.2018.1523738Peck J., Theodore N. Fast policy: experimental statecraft at the thresholds of neoliberalism. U.S.: University of Minnesota press, 2015. Mode of access: http://ebookcentral.proquest.com/lib/UWSAU/detail.action?docID=205050 (accessed: 28.08.2020).Peck J., Theodore N. Fast policy: experimental statecraft at the thresholds of neoliberalism. U.S.: University of Minnesota press, 2015. Mode of access: http://ebookcentral.proquest.com/lib/UWSAU/detail.action?docID=205050 (accessed: 28.08.2020).Plesner U. An actor-network perspective on changing work practices: Communication technologies as actants in newswork. Journalism. 2009, Vol. 10, N 5, P. 604-626. DOI: 10.1177/1464884909106535Plesner U. An actor-network perspective on changing work practices: Communication technologies as actants in newswork. Journalism. 2009, Vol. 10, N 5, P. 604-626. DOI: 10.1177/1464884909106535Potseluev S.P., Konstantinov M.S., Podshibyakina T.A. Stratecies of cognitive political censorship as an effect "new media". Dilemas contemporaneous: educacion, politica y valores. 2020, Vol. 7, N 2, P. 91. DOI: 10.46377/dilemas.v33i1.2186 EDN: UXGNCZPotseluev S.P., Konstantinov M.S., Podshibyakina T.A. Stratecies of cognitive political censorship as an effect "new media". Dilemas contemporaneous: educacion, politica y valores. 2020, Vol. 7, N 2, P. 91. DOI: 10.46377/dilemas.v33i1.2186 EDN: UXGNCZRodriguez M.G., Balduzzi D., Schölkopf B. Uncovering the temporal dynamics of diffusion networks. arXiv preprint arXiv:1105.0697. 2011. Mode of access: https://arxiv.org/abs/1105.0697 (accessed: 02.07.2021).Rodriguez M.G., Balduzzi D., Schölkopf B. Uncovering the temporal dynamics of diffusion networks. arXiv preprint arXiv:1105.0697. 2011. Mode of access: https://arxiv.org/abs/1105.0697 (accessed: 02.07.2021).Schaefer, D.R., Marcum, C.S. Modeling network dynamics. In: The Oxford handbook of social networks. 2017, P. 254-287.Schaefer, D.R., Marcum, C.S. Modeling network dynamics. In: The Oxford handbook of social networks. 2017, P. 254-287.Shields R. Flow as a new paradigm. Space and culture. 1997, Vol. 1, N 1, P. 1-7. DOI: 10.1177/120633129700100101Shields R. Flow as a new paradigm. Space and culture. 1997, Vol. 1, N 1, P. 1-7. DOI: 10.1177/120633129700100101Snijders T.A.B. Stochastic actor-oriented models for network dynamics. Annual review of statistics and its application. 2017, Vol. 4, P. 343-363. DOI: 10.1146/annurev-statistics-060116-054035Snijders T.A.B. Stochastic actor-oriented models for network dynamics. Annual review of statistics and its application. 2017, Vol. 4, P. 343-363. DOI: 10.1146/annurev-statistics-060116-054035Suitor J.J., Wellman B., Morgan D.L. It's about time: how, why, and when networks change. Social networks. 1997, Vol. 19, N 1, P. 1-7. DOI: 10.1016/s0378-8733(96)00287-0Suitor J.J., Wellman B., Morgan D.L. It's about time: how, why, and when networks change. Social networks. 1997, Vol. 19, N 1, P. 1-7. DOI: 10.1016/s0378-8733(96)00287-0Valente T.W. Network models of the diffusion of innovations. Computational and mathematical organization theory. 1996, Vol. 2, N 2, P. 163-164. DOI: 10.1007/bf00240425Valente T.W. Network models of the diffusion of innovations. Computational and mathematical organization theory. 1996, Vol. 2, N 2, P. 163-164. DOI: 10.1007/bf00240425Иванов Д.В. Новый подход к оценке социального развития // Социологические исследования. - 2021. - № 1. - С. 50-62. -. DOI: 10.31857/S013216250010462-1 EDN: MWGJMRIvanov D.V. New approach to assessment of social development. Sociological studies. 2021, N 1, P. 50–62. DOI: https://doi.org/10.31857/S013216250010462-1 (In Russ.)Сморгунов Л.В. Сетевая теория политики и управления // Современная политическая теория. Методология / под ред. О.В. Гаман-Голутвиной, А.И. Никитина. - М.: Издательство "Аспект Пресс", 2017. - С. 233-261.Smorgunov L.V. Network theory of politics and management. In: Gaman-Golutvina O.V., Nikitin A.I. (eds). Modern political theory. Methodology. Moscow : Aspect Press, 2017, P. 233–261. (In Russ.)

The authors declare that there are no conflicts of interest present.