Abstract
We develop and analyze an agent-based model for the study of information propagation in dynamic contact networks. We represent information as a state of a node in a network that can be probabilistically transferred to an adjacent node within a single time step. The model is based on a closed (yet sufficiently large) population that can support processes of link generation and annihilation using different contact regimes. Our study is confined to the case of homogeneous contacts, where each agent establishes and breaks contacts in the same way. We consider information to be available for spreading in a fixed time window (i.e. finite memory). We find, surprisingly, that information transmission (measured as the proportion of informed nodes after a fixed number of time steps) is identical for dynamic preferential and random networks, but radically different for the associate mixing contact regime. We also find that the probability of transmission is, similarly counterintuitively, not a main driver of the process as opposed the the main network par maters determining contact lifetime and the turnover rate on connections. We discuss the explanation and the significance of these results in the light of the fundamental difference between dynamic and static (cumulative) networks.
Similar content being viewed by others
References
M. Newman, Networks: an introduction (Oxford University Press, Inc., 2010)
S.N. Dorogovtsev, Lectures on complex networks (Oxford University Press, 2010)
D. Easley, J. Kleinberg, Networks, crowds, and markets (Cambridge University Press, 2010)
R. Cohen, S. Havlin, Complex networks: structure, robustness and function (Cambridge University Press, 2010)
B. Bollobás, R. Kozma, D. Miklos, Handbook of large-scale random networks, Vol. 18 (Springer, 2009)
P.S. Bearman, J. Moody, K. Stovel, Amer. J. Sociol. 110, 44 (2004)
L. Gulyás, S. Khor, R. Legéndi, G. Kampis, Elementary dynamic networks. In Sunbelt XXXI, International Sunbelt Social Network Conference, St. Pete Beach, FL (2011)
L. Isella, J. Stehlé, A. Barrat, C. Cattuto, J.F. Pinton, W. Van den Broeck, J. Theoretical Biol. 271, 166 (2011)
L. Isella, M. Romano, A. Barrat, C. Cattuto, V. Colizza, W. Van den Broeck, F. Gesualdo, E. Pandolfi, L. Ravà, C. Rizzo, et al., PLoS One 6, e17144 (2011)
M. Morris, H. Epstein, M. Wawer, PLoS One 5, e14092 (2010)
M. Morris, A.E. Kurth, D.T. Hamilton, J. Moody, S. Wakefield, Amer. J. Public Health 99, 1023 (2009)
M.J. Keeling, K.T.D. Eames, J. Royal Soc. Interf. 2, 295 (2005)
R.A. Stein, Int. J. Infect. Diseases 15, e510 (2011)
P.M.A. Sloot, S.V. Ivanov, A.V. Boukhanovsky, D.A.M.C. Van De Vijver, C.A.B. Boucher, Int. J. Computer Math. 85, 1175 (2008)
S. Mei, P.M.A. Sloot, R. Quax, Y. Zhu, W. Wang, Math. Computers Simul. 80, 1018 (2010)
R.O. Legendi, L. Gulyas, Effects of time-dependent edge dynamics on properties of cumulative networks, EPNACS-Emergent Properties in Natural and Artificial Complex Systems (2011)
L. Gulyás, G. Kampis, R. Legéndi, Eur. Phys. J. Special Topics 222 (6), 1311 (2013)
G. Kampis, L. Gulyás, NetSci 2010 The International School and Conference on Network Science, 10 (2010)
R.K. Merton, Science 159, 56 (1968)
P.L. Krapivsky, S. Redner, Phys. Review E 63, 066123 (2001)
P.L. Krapivsky, S. Redner, Stat. Mech. Complex Networks, 3 (2003)
R. Albert, A.L. Barabási, Rev. Modern Phys. 74, 47 (2002)
A.L. Barabási, R. Albert, Science 286, 509 (1999)
P. Erdos, A. Rényi, Publ. Math. 6, 290 (1959)
P. Erdos, A. Rényi, Magyar Tud. Akad. Mat. Kutató Int. Közl 5, 17 (1960)
B. Bollobás, Random graphs, Vol. 73 (Cambridge University Press, 2001)
M.E.J. Newman, Phys. Rev. Lett. 89, 208701 (2002)
M. McPherson, L. Smith-Lovin, J.M. Cook, Ann. Rev. Sociol. 415 (2001)
S.M. Goodreau, J.A. Kitts, M. Morris, Demography 46, 103 (2009)
M. Girvan, M.E.J. Newman, Proc. National Acad. Sci. 99, 7821 (2002)
U. Wilensky, Netlogo, http://ccl.northwestern.edu/netlogo. Evanston, IL: Northwestern university. Center for Connected Learning and Computer-Based Modeling (1999)
T. Máhr, R. Bocsi, L. Gulyás, Simulation as a service: The model exploration service. In 3rd World Congress on Social Simulation, Kassel, Germany (2010)
M. Iványi, L. Gulyás, R. Bocsi, G. Szemes, R. Mészáros, Model exporation module. In Agent 2007: Complex Interaction and Social Emergence Conference, Evanston, IL, November 15–18 (2010)
L. Gulyás, A. Szabó, R. Legéndi, T. Máhr, R. Bocsi, G. Kampis, Tools for large scale (distributed) agent-based computational experiments. 2011 Computational Social Science Society of America Annual Conference, Santa Fe, NM, USA (2012)
F. Liljeros, C.R. Edling, L.A.N.A Amaral, E.H. Stanley, Y. Åberg, Nature 411, 907 (2001)
N. Zarrabi, M. Prosperi, R.G. Belleman, M. Colafigli, A. De Luca, P.M.A. Sloot, PloS one 7, e46156 (2012)
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
About this article
Cite this article
Gulyás, L., Kampis, G. Spreading processes on dynamically changing contact networks. Eur. Phys. J. Spec. Top. 222, 1359–1376 (2013). https://doi.org/10.1140/epjst/e2013-01931-y
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1140/epjst/e2013-01931-y