Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Competitive cluster growth in complex networks.

André A Moreira1, Demétrius R Paula, Raimundo N Costa Filho

  • 1Departamento de Física, Universidade Federal do Ceará, 60451-970 Fortaleza, Ceará, Brazil.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|August 16, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Allometric scaling of brain activity explained by avalanche criticality.

Journal of the Royal Society, Interface·2026
Same author

Evolving spatiotemporal patterns and urban scaling of deaths from external causes.

Scientific reports·2026
Same author

Critical exponents for isotropically directed percolation on hierarchical lattices.

Physical review. E·2025
Same author

Channel instability in binary mixtures with differential diffusivity.

Soft matter·2025
Same author

The impact of COVID-19 mobility restrictions on dengue transmission in urban areas.

PLoS neglected tropical diseases·2024
Same author

Tunable disorder on the S-state majority-voter model.

Chaos (Woodbury, N.Y.)·2024
Same journal

Tension on dsDNA bound to ssDNA-RecA filaments may play an important role in driving efficient and accurate homology recognition and strand exchange.

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Amplitude-phase coupling drives chimera states in globally coupled laser networks [Phys. Rev. E 91, 040901(R) (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Shapes of sedimenting soft elastic capsules in a viscous fluid [Phys. Rev. E 92, 033003 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Attenuation of excitation decay rate due to collective effect [Phys. Rev. E 90, 022142 (2014)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Role of connectivity and fluctuations in the nucleation of calcium waves in cardiac cells [Phys. Rev. E 92, 052715 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Lattice Boltzmann approach for complex nonequilibrium flows [Phys. Rev. E 92, 043308 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
See all related articles

We introduce a model for competitive cluster growth in complex networks. Network topology influences cluster size distribution, mirroring electoral vote patterns on hierarchical networks.

Area of Science:

  • Complex systems
  • Network science
  • Sociophysics

Background:

  • Understanding community formation and opinion dynamics is crucial in social networks.
  • Competitive cluster growth models help analyze how groups form and evolve.
  • Network topology significantly impacts emergent behaviors within agent-based systems.

Purpose of the Study:

  • To propose an idealized model for competitive cluster growth in complex networks.
  • To investigate the influence of network topology on cluster size distribution.
  • To explore the applicability of the model to real-world phenomena like electoral processes.

Main Methods:

  • Development of an idealized mathematical model for cluster growth.
  • Simulation of the growth process on various network topologies.

Related Experiment Videos

  • Analysis of cluster size distributions and their scaling properties.
  • Comparison of model-derived distributions with empirical data from electoral processes.

    • Main Results:

    • The cluster size distribution is contingent upon the specific network topology.
    • Hierarchical networks, such as the Apollonian network, yield cluster size distributions with a scaling form.
    • This observed scaling form resembles distributions found in electoral vote counts.

    Conclusions:

    • Network topology is a key determinant of competitive cluster growth dynamics.
    • Hierarchical structures in social networks may explain observed scaling patterns in electoral processes.
    • The proposed model offers insights into opinion formation and community evolution in complex systems.