Abstract
The evolutionary process of social networking is a transition from one state to another through chaos that features high system sensitivity to external disturbances. Thus, a system may be in a certain stable state called an attractor adversely affected by a potential threat to social networking actors. So let us have synergetic control conceptualized here in terms of social network actors’ interactions control to ensure national information security. The design of a synergetic system to control self-organizing virtual communities enables a chaos-control transition thus achieving the predicted result of their actors’ interactions. There are some models introduced.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Horbulin, V.P., Dodonov, O.H., Lande, D.V.: Informatsiini operatsii ta bezpeka suspilstva: zahrozy, protydiia, modeliuvannia. Intertekhnolohiia, Kyiv (2009)
Tatnall, A.: Actor-Network Theory and Technology Innovation: Advancements and New Concepts. Information Science Reference, New York (2010)
Rogers, E.M.: Diffusion of Innovations. Free Press, New York (2003)
Castells, M., Cardoso, G.: The Network Society: From Knowledge to Policy. Johns Hopkins Center for Transatlantic Relations, Washington (2005)
Epstein, J.M.: Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton (2012)
Epstein, J.M.: Nonlinear Dynamics, Mathematical Biology, and Social Science: Lecture Notes. Addison-Wesley Publishing Company, Massachusetts (1997)
Barrett, C., Eubank, S., Marathe, M.: Modeling and simulation of large biological, information and socio-technical systems: an interaction based approach. In: Goldin, D., Smolka, S.A. (eds.) Interactive Computation, pp. 353–392. Springer, Heidelberg (2006)
Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)
Missaoui, R., Sarr, I.: Social Network Analysis - Community Detection and Evolution. Springer International Publishing, Switzerland (2014)
Tabor, M.: Chaos and Integrability in Nonlinear Dynamics: An Introduction. Wiley, Michigan (1989)
Kolesnikov, A.A.: Sinergeticheskoe metody upravlenija slozhnymi sistemami: teorija sistemnogo sinteza. Editorial URSS, Moskow (2005)
Prigogine, I., Stengers, I.: Order Out of Chaos. Man’s New Dialogue with Nature. Heinemann, London (1984)
Haken, H.: Advanced Synergetics: Instability Hierarchies of Self-Organizing Systems and Devices. Springer-Verlag, New York (1993)
Serikov, A.V.: Jeffektivnost’ hozjajstvennoj dejatel’nosti: opredelenie, izmerenie, sinergeticheskoe upravlenie. Ekonomichnyi visnyk Donbasu 2(24), 212–219 (2011)
Hryshchuk, R.V.: Kontseptsiia pobudovy dyferentsialno-ihrovykh harantovano zakhyshchenykh rozpodilenykh system zakhystu informatsii. Suchasnyi zakhyst informatsii 1(6), 4–9 (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Hryshchuk, R., Molodetska, K. (2017). Synergetic Control of Social Networking Services Actors’ Interactions. In: Szewczyk, R., Kaliczyńska, M. (eds) Recent Advances in Systems, Control and Information Technology. SCIT 2016. Advances in Intelligent Systems and Computing, vol 543. Springer, Cham. https://doi.org/10.1007/978-3-319-48923-0_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-48923-0_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48922-3
Online ISBN: 978-3-319-48923-0
eBook Packages: EngineeringEngineering (R0)