Skip to main content

Synergetic Control of Social Networking Services Actors’ Interactions

  • Conference paper
  • First Online:
Recent Advances in Systems, Control and Information Technology (SCIT 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 543))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Horbulin, V.P., Dodonov, O.H., Lande, D.V.: Informatsiini operatsii ta bezpeka suspilstva: zahrozy, protydiia, modeliuvannia. Intertekhnolohiia, Kyiv (2009)

    Google Scholar 

  2. Tatnall, A.: Actor-Network Theory and Technology Innovation: Advancements and New Concepts. Information Science Reference, New York (2010)

    Google Scholar 

  3. Rogers, E.M.: Diffusion of Innovations. Free Press, New York (2003)

    Google Scholar 

  4. Castells, M., Cardoso, G.: The Network Society: From Knowledge to Policy. Johns Hopkins Center for Transatlantic Relations, Washington (2005)

    Google Scholar 

  5. Epstein, J.M.: Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton (2012)

    Google Scholar 

  6. Epstein, J.M.: Nonlinear Dynamics, Mathematical Biology, and Social Science: Lecture Notes. Addison-Wesley Publishing Company, Massachusetts (1997)

    MATH  Google Scholar 

  7. 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)

    Chapter  Google Scholar 

  8. Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)

    Book  MATH  Google Scholar 

  9. Missaoui, R., Sarr, I.: Social Network Analysis - Community Detection and Evolution. Springer International Publishing, Switzerland (2014)

    Book  Google Scholar 

  10. Tabor, M.: Chaos and Integrability in Nonlinear Dynamics: An Introduction. Wiley, Michigan (1989)

    MATH  Google Scholar 

  11. Kolesnikov, A.A.: Sinergeticheskoe metody upravlenija slozhnymi sistemami: teorija sistemnogo sinteza. Editorial URSS, Moskow (2005)

    Google Scholar 

  12. Prigogine, I., Stengers, I.: Order Out of Chaos. Man’s New Dialogue with Nature. Heinemann, London (1984)

    Google Scholar 

  13. Haken, H.: Advanced Synergetics: Instability Hierarchies of Self-Organizing Systems and Devices. Springer-Verlag, New York (1993)

    MATH  Google Scholar 

  14. Serikov, A.V.: Jeffektivnost’ hozjajstvennoj dejatel’nosti: opredelenie, izmerenie, sinergeticheskoe upravlenie. Ekonomichnyi visnyk Donbasu 2(24), 212–219 (2011)

    Google Scholar 

  15. Hryshchuk, R.V.: Kontseptsiia pobudovy dyferentsialno-ihrovykh harantovano zakhyshchenykh rozpodilenykh system zakhystu informatsii. Suchasnyi zakhyst informatsii 1(6), 4–9 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ruslan Hryshchuk .

Editor information

Editors and Affiliations

Rights and permissions

Reprints 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)

Publish with us

Policies and ethics