TY - JOUR
T1 - Review mechanism promotes knowledge transmission in complex networks
AU - Wang, Haiying
AU - Wang, Jun
AU - Small, Michael
AU - Moore, Jack Murdoch
N1 - Publisher Copyright:
© 2018 Elsevier Inc.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Knowledge transmission systems differ from epidemic spreading systems in that people who have forgotten knowledge can reacquire it through reviewing. In order to analyze the review mechanism, we propose a Naive-Evangelical-Agnostic (VEA) knowledge transmission model in complex networks. Specifically, we derive a knowledge transmission system in homogeneous and heterogeneous networks, respectively. Mean field theory is used to theoretically delineate the knowledge transmission systems. In homogeneous networks, the steady state solution of the system is obtained. In heterogeneous networks, we get the basic reproduction number R0, in which the reviewing rate is an important parameter. Moreover, we analyze the system and prove that if R0 < 1, the knowledge loss equilibrium of the model is globally asymptotically stable; if R0 > 1, the knowledge is permanent. In addition, to complement the theoretical analysis, numerical simulations are performed in four representative network models: random regular, small world, random growth and scale free networks. The simulation results indicate that the review mechanism has a clear positive influence for the knowledge transmission in the four networks, i.e., a higher reviewing rate leads to a higher final density of evangelical nodes. In addition, the simulation results illustrate that scale free networks transfer knowledge faster than the other three networks.
AB - Knowledge transmission systems differ from epidemic spreading systems in that people who have forgotten knowledge can reacquire it through reviewing. In order to analyze the review mechanism, we propose a Naive-Evangelical-Agnostic (VEA) knowledge transmission model in complex networks. Specifically, we derive a knowledge transmission system in homogeneous and heterogeneous networks, respectively. Mean field theory is used to theoretically delineate the knowledge transmission systems. In homogeneous networks, the steady state solution of the system is obtained. In heterogeneous networks, we get the basic reproduction number R0, in which the reviewing rate is an important parameter. Moreover, we analyze the system and prove that if R0 < 1, the knowledge loss equilibrium of the model is globally asymptotically stable; if R0 > 1, the knowledge is permanent. In addition, to complement the theoretical analysis, numerical simulations are performed in four representative network models: random regular, small world, random growth and scale free networks. The simulation results indicate that the review mechanism has a clear positive influence for the knowledge transmission in the four networks, i.e., a higher reviewing rate leads to a higher final density of evangelical nodes. In addition, the simulation results illustrate that scale free networks transfer knowledge faster than the other three networks.
KW - Complex networks
KW - Equilibrium
KW - Knowledge transmission
KW - Review mechanism
UR - https://www.scopus.com/pages/publications/85053039901
U2 - 10.1016/j.amc.2018.07.051
DO - 10.1016/j.amc.2018.07.051
M3 - 文章
AN - SCOPUS:85053039901
SN - 0096-3003
VL - 340
SP - 113
EP - 125
JO - Applied Mathematics and Computation
JF - Applied Mathematics and Computation
ER -