Abstract
An innovative approach for analysis of “network society” with its large- scale and multicomponent features has been proposed. A new network model - a model of so-called aggregate networks has been developed as a key tool for such analysis. These aggregate structures topologically are not identical in their global and local scales, and thus distinguished from canonical large-scale networks. It was elicited that aggregate network entities have significant features in their topological vulnerability in comparison with canonical ones. This is crucial for building resilient constructions of the network society. Also some additional distinctions for the concepts of “network” and “graph” have been formulated.
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References
Barney, D.D.: The Network Society, p. 216. Polity Press, Malden (2004)
Castells, M.: Informationalism, networks, and the network society: a theoretical blueprint. Edward Elgar, Northampton (2004)
van Dijk, J.: Outline of a multilevel theory of the network society, http://www.utwente.nl/gw/vandijk/research/network_theory/network_theory_plaatje/a_theory_outline_outline_of_a/
Li, W., Bashan, A., Buldyrev, S.V., Stanley, H.E., Havlin, S.: Cascading Failures in Interdependent Lattice Networks: The Critical Role of the Length of Dependency Links. Physical Review Letters PRL 108, 228702 (2012)
Gomez-Gardenes, J., Reinares, I., Arenas, A., Floria, L.M.: Evolution of Cooperation in Multiplex Networks. Sci. Rep. 2, 620 (2012), http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3431544/pdf/srep00620.pdf
Frivolt, G.: Analysis of Massive Networks. In: Bielikova, M. (ed.) IIT.SRC, pp. 35–40 (2005)
Perumal, S., Basu, P., Guan, G.: Minimizing Eccentricity in Composite Networks via Constrained Edge Additions. In: MILCOM 2013, San Diego, CA (November 2013), http://www.ir.bbn.com/~pbasu/pubs/milcom2013-composite.pdf
Leskovec, J.: Dynamics of large networks. PhD Dissertation. Carnegie Mellon University. Technical report CMU-ML-08-111 (2008)
Aminova, M., Rossodivita, A., Tikhomirov, A., Trufanov, A.: Comprehensive network lace (how to govern the world). Proceedings of Free Economic Society of Russia 148, 190–207 (2011), http://www.iuecon.org/2011/148/20VEOR_PRINT.pdf
Frye, L., Cheng, L., Heflin, J.: An Ontology-Based System to Identify Complex Network Attacks. In: First IEEE International Workshop on Security and Forensics in Communication Systems, part of IEEE International Conference on Communications 2012, Ottawa, Canada (2012), http://swat.cse.lehigh.edu/pubs/frye12a.pdf
Graph-tool, http://graph-tool.skewed.de/
Dunbar, R.I.M.: Neocortex size as a constraint on group size in primates. Journal of Human Evolution 22(6), 469–493 (1992)
Igraph, http://igraph.org/python/
Matplotlib Pyplot, http://matplotlib.org/api/pyplot_api.html
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Tikhomirov, A. et al. (2014). Network Society: Aggregate Topological Models. In: Dudin, A., Nazarov, A., Yakupov, R., Gortsev, A. (eds) Information Technologies and Mathematical Modelling. ITMM 2014. Communications in Computer and Information Science, vol 487. Springer, Cham. https://doi.org/10.1007/978-3-319-13671-4_47
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DOI: https://doi.org/10.1007/978-3-319-13671-4_47
Publisher Name: Springer, Cham
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