Organization of growing random networks.
- P. Krapivsky, S. Redner
- Computer SciencePhysical review. E, Statistical, nonlinear, and…
- 6 November 2000
The organizational development of growing random networks is investigated, and the combined age and degree distribution of nodes shows that old nodes typically have a large degree.
A Kinetic View of Statistical Physics
- P. Krapivsky, S. Redner, E. Ben-Naim
- Physics
- 2010
1. Aperitifs 2. Diffusion 3. Collisions 4. Exclusion 5. Aggregation 6. Fragmentation 7. Adsorption 8. Spin dynamics 9. Coarsening 10. Disorder 11. Hysteresis 12. Population dynamics 13. Diffusive…
Connectivity of growing random networks.
- P. Krapivsky, S. Redner, F. Leyvraz
- MathematicsPhysical Review Letters
- 8 May 2000
A solution for the time- and age-dependent connectivity distribution of a growing random network is presented and the power law N(k) approximately k(-nu) is found, where the exponent nu can be tuned to any value in the range 2.
Dynamics of social balance on networks.
- T. Antal, P. Krapivsky, S. Redner
- Computer SciencePhysical review. E, Statistical, nonlinear, and…
- 19 June 2005
This work studies the evolution of social networks that contain both friendly and unfriendly pairwise links between individual nodes, and finds that an infinite network undergoes a dynamic phase transition from a steady state to "paradise" as the propensity p for friendly links in an update event passes through 1/2.
Social balance on networks : The dynamics of friendship and enmity
- T. Antal, P. Krapivsky, S. Redner
- Computer Science
- 21 May 2006
Degree distributions of growing networks.
- P. Krapivsky, G. J. Rodgers, S. Redner
- Computer SciencePhysical Review Letters
- 11 December 2000
The in-degree and out-degree distributions of a growing network model are determined by tuning the parameters in these rates to reasonable values, exponents which agree with those of the web graph are obtained.
Network growth by copying.
- P. Krapivsky, S. Redner
- Computer SciencePhysical review. E, Statistical, nonlinear, and…
- 17 March 2005
A growing network model in which a new node attaches to a randomly selected node, as well as to all ancestors of the target node, produces a sparse, ultrasmall network where the average node degree grows logarithmically with network size while the network diameter equals 2.
Bifurcations and patterns in compromise processes
- E. Ben-Naim, P. Krapivsky, S. Redner
- Mathematics
- 13 December 2002
Stochastic Theory of Early Viral Infection: Continuous versus Burst Production of Virions
- J. Pearson, P. Krapivsky, A. Perelson
- BiologyPLoS Comput. Biol.
- 1 February 2011
In stochastic models of viral infection the two modes of viral production yield different early term dynamics, and the probability that infections initiated with any number of virions and infected cells reach extinction is analytically determined.
Dynamics of majority rule in two-state interacting spin systems.
- P. Krapivsky, S. Redner
- Economics, MathematicsPhysical Review Letters
- 11 March 2003
A two-state opinion dynamics model where agents evolve by majority rule is introduced, where a group of agents is specified whose members then all adopt the local majority state.
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