메뉴 건너뛰기




Volumn 117, Issue 22, 2016, Pages

Continuous-Time Discrete-Distribution Theory for Activity-Driven Networks

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMICAL SYSTEMS; EPIDEMIOLOGY; NONLINEAR DYNAMICAL SYSTEMS;

EID: 84999143152     PISSN: 00319007     EISSN: 10797114     Source Type: Journal    
DOI: 10.1103/PhysRevLett.117.228302     Document Type: Article
Times cited : (67)

References (40)
  • 3
    • 84866939709 scopus 로고    scopus 로고
    • P. Holme and J. Saramäki, Phys. Rep. 519, 97 (2012). PRPLCM 0370-1573 10.1016/j.physrep.2012.03.001
    • (2012) Phys. Rep. , vol.519 , pp. 97
    • Holme, P.1    Saramäki, J.2
  • 29
    • 84999145847 scopus 로고    scopus 로고
    • The relationship with discrete-time ADN models is straightforward. In a time step (Equation presented), the continuous-time model establishes as many edges as in a realization of the discrete-time model. The activity rate of a node in continuous time corresponds to the product of its activity potential and the number of contacts it can establish in the time step. The probability that an infected node recovers in a discrete-time step is (Equation presented). The per-contact infection probability does not change between continuous and discrete time.
    • The relationship with discrete-time ADN models is straightforward. In a time step (Equation presented), the continuous-time model establishes as many edges as in a realization of the discrete-time model. The activity rate of a node in continuous time corresponds to the product of its activity potential and the number of contacts it can establish in the time step. The probability that an infected node recovers in a discrete-time step is (Equation presented). The per-contact infection probability does not change between continuous and discrete time.
  • 30
    • 84999171967 scopus 로고    scopus 로고
    • The original formulation of ADNs posits a continuous power-law distribution with (Equation presented).
    • The original formulation of ADNs posits a continuous power-law distribution with (Equation presented).
  • 32
    • 84999208222 scopus 로고    scopus 로고
    • See Supplemental Material at for details about the derivation of the main equations, employed mathematical tools, parameter identification for the case studies, and finite-time horizon predictions for the Twitter case study.
    • See Supplemental Material at http://link.aps.org/supplemental/10.1103/PhysRevLett.117.228302 for details about the derivation of the main equations, employed mathematical tools, parameter identification for the case studies, and finite-time horizon predictions for the Twitter case study.
  • 34


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.