Dynamics on networks: Competition of temporal and topological correlations

Scientific Reports

Volumn 7, Issue , 2017, Pages

  Artime, Oriol ^a   Ramasco, José J ^a   San Miguel, Maxi ^a  

^a UNIVERSITAT DE LES ILLES BALEARS   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85011579210     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep41627     Document Type: Article

References (51)

1. Newman, M. E. J. Networks: An introduction (Oxford University Press, Oxford, UK, 2010).
2. Barrat, A., Barthelemy, M. & Vespignani, A. Dynamical processes on complex networks (Cambridge University Press, 2008).
3. Pastor-Satorras, R. & Vespignani, A. Epidemic spreading in scale-free networks. Physical Review Letters 86, 3200 (2001).
4. Barthelemy, M., Pastor-Satorras, R. & Vespignani, A. The architecture of complex weighted networks. Proceedings of the National Academy of Science USA 101, 3747 (2004).
5. Kivelä, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y. & Porter, M. A. Multilayer networks. Journal of complex networks 2, 203 (2014).
6. Diakonova, M., Nicosia, V., Latora, V. & San Miguel, M. Irreducibility of multilayer network dynamics: The case of the voter model. New Journal of Physics 18, 023010 (2016).
7. Wang, Z., Zhao, D., Wang, L., Sun, G. & Jin, Z. Immunity of multiplex networks via acquaintance vaccination. Europhysics Letters 112, 48002 (2015).
8. Wang, Z. et al. Statistical physics of vaccination. Physics Reports 664, 1 (2016).
9. Zhao, D. et al. Immunization of epidemics in multiplex networks. PloS one 9, e112018 (2014).
10. Cattuto, C. et al. Dynamics of person-To-person interactions from distributed RFID sensor networks. Plos ONE 5, 11596 (2010).
11. Miritello, G., Moro, E. & Lara, R. Dynamical strength of social ties in information spreading. Physical Review E 83, 045102(R) (2011).
12. Holme, P. & Saramäki, J. Temporal networks. Physics Reports 519, 97 (2012).
13. Gauvin, L., Panisson, A., Cattuto, C. & Barrat, A. Activity clocks: spreading dynamics on temporal networks of human contact. Scientific Reports 3, 3099 (2013).
14. Machens, A. et al. An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matrices. BMC Infectious Diseases 13, 185 (2013).
15. Karsai, M., Perra, N. & Vespignani, A. Time varying networks and the weakness of strong ties. Scientific Reports 4 (2014).
16. Vestergaard, C. L., Génois, M. & Barrat, A. How memory generates heterogeneous dynamics in temporal networks. Physical Review E 90, 207 (2014).
17. Barabási, A.-L. The origin of bursts and heavy tails in human dynamics. Nature 435, 207-211 (2005).
18. Oliveira, J. G. & Barabási, A.-L. Human dynamics: Darwin and Einstein correspondence patterns. Nature 437, 1251 (2005).
19. Vazquez, A. et al. Modeling bursts and heavy tails in human dynamics. Physical Review E 73, 036127 (2006).
20. Vazquez, A., Racz, B., Lukacs, A. & Barabási, A.-L. Impact of non-Poissonian activity patterns on spreading processes. Physical Review Letters 98, 158702 (2007).
21. Gonçalves, B. & Ramasco, J. J. Human dynamics revealed through Web analytics. Physical Review E 78 026123 (2008).
22. Oliveira, J. G. & Vazquez, A. Impact of interactions on human dynamics. Physica A 388 187-192 (2009).
23. Iribarren, J. L. & Moro, E. Impact of human activity patterns on the dynamics of information diffusion. Physical Review Letters 103 038702 (2009).
24. Radicchi, F. Human activity in the web. Physical Review E 80, 026118 (2009).
25. Meiss, M., Duncan, J., Gonçalves, B., Ramasco, J. J. & Menczer, F. Whats in a session: Tracking individual behavior on the web. Proceedings of the 20th ACM conference on Hypertext and hypermedia (ACM) 173-182 (2009).
26. Fernández-Gracia, J., Eguluz, V. M. & San Miguel, M. Update rules and inter-event time distributions: Slow ordering versus no ordering in the voter model. Physical Review E 84, 015103 (2011).
27. Perra, N., Gonçalves, B., Pastor-Satorras, R. & Vespignani, A. Activity driven modeling of time varying networks. Scientific Reports 2, 469 (2012).
28. Stark, H.-U., Tessone, C. J. & Schweitzer, F. Decelerating microdynamics can accelerate macrodynamics in the voter model. Physical Review Letters 101, 018701 (2008).
29. Onnela, J.-P. et al. Structure and tie strengths in mobile communication networks. Proceedings of the National Academy of Sciences USA 104, 7332 (2007).
30. Karsai, M. et al. Small but slow world: How network topology and burstiness slow down spreading. Physical Review E 83, 025102 (2011).
31. Takaguchi, T. & Masuda, N. Voter model with non-Poissonian inter-event times. Physical Review E 84, 036115 (2011).
32. Liu, S., Perra, N., Karsai, M. & Vespignani, A. Controlling contagion processes in activity driven networks. Phys. Rev. Lett. 112, 118702 (2014).
33. Delvenne, J.-C., Lambiotte, R. & Rocha, L. E. Diffusion on networked systems is a question of time or structure. Nature Communications 6 (2015).
34. Sun, K., Baronchelli, A. & Perra, N. Contrasting effects of strong ties on SIR and SIS processes in temporal networks. The European Physical Journal B 88, 1 (2015).
35. Goh, K.-I. & Barabási, A.-L. Burstiness and memory in complex systems. Europhysics Letters 81, 48002 (2008).
36. Miritello, G., Lara, R. & Moro, E. ime allocation in social networks: correlation between social structure and human communication dynamics. Temporal Networks. Springer, Heidelberg, Germany (2013).
37. Toivonen, R. et al. Broad lifetime distributions for ordering dynamics in complex networks. Physical Review E 79 (2009).
38. Rosvall, M., Esquivel, A. V., Lancichinetti, A., West, J. D. & Lambiotte, R. Memory in network flows and its effects on spreading dynamics and community detection. Nature Communications 5 (2014).
39. Scholtes, I. et al. Causality-driven slow-down and speed-up of diffusion in non-Markovian temporal networks. Nature Communications 5 (2014).
40. Scholtes, I., Wider, N. & Garas, A. Higher-order aggregate networks in the analysis of temporal networks: path structures and centralities. The European Physical Journal B 89, 3, 1-15 (2016).
41. Ubaldi, E., Vezzani, A., Karsai, M., Perra, N. & Burioni, R. Burstiness and tie reinforcement in time varying social networks. arXiv preprint arXiv:1607.08910 (2016).
42. Lambiotte, R., Salnikov, V. & Rosvall, M. Effect of memory on the dynamics of random walks on networks. Journal of Complex Networks 3, 177 (2015).
43. Rosvall, M. & Berstrom, C. T. Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences USA 105, 1118 (2008).
44. Lancichinetti, A., Fortunato, S. & Radicchi, F. Benchmark graphs for testing community detection algorithms. Physical Review E 78, 046110 (2008).
45. Ramasco, J. J. & Gonçalves, B. Transport on weighted networks: When the correlations are independent of the degree. Physical Review E 76 (2007).
46. Daley, D. J., Gani, J. & Gani, J. M. Epidemic modelling: An introduction Volume 15, Cambridge University Press (2001).
47. Ligget, T. M. Stochastic interacting systems: contact, voter and exclusion processes. Springer Science & Business Media (1999).
48. Suchecki, K., Eguluz, V. M. & San Miguel, M. Voter model dynamics in complex networks: Role of dimensionality, disorder, and degree distribution. Physical Review E 72 (2005).
49. Castelló, X. et al. Anomalous lifetime distributions and topological traps in ordering dynamics. Europhysics Letters 79, 66006 (2007).
50. Masuda, N. Voter model on the two-clique graph. Physical Review E 90 (2014).
51. Wu, Z., Braunstein, L. A., Havlin, S. & Stanley, H. E. Transport in weighted networks: partition into superhighways and roads. Physical Review Letters 96, 148702 (2006).