Information Technology Reference
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3.7 Conclusion
We have in this chapter discussed the diffusion process of information on scale-free
networks. Analytical methods for information diffusion suggest that PDE can solve
the diffusion phenomena approximately in Euclidean spaces, although the calculus
on networks or discrete spaces have been proposed. On the other hand, computa-
tional methods can be applied to investigate the process of information diffusion
using a large-scale simulation performed on personal desktop computers.
In the results of our simulation, we have observed that the process of information
diffusion obeys a certain property of growth curves, and that there may be several
quantum leaps which are caused by the hubs of social networks. Adding to that, we
have discovered the results of dissipative effect using two operations for the
network in our simulation. One is eliminating the main hub from the networks,
the other is reconstructing the network as stochastic networks with a constant
diffusion probability. The former operation can decrease the number of quantum
leaps in the process of information diffusion, whereas the latter operation can delay
the process dependent on the structure of stochastic networks. We can conclude that
the effect of eliminating the main hub from the network is similar to that of a
probabilistic diffusion process with the probability between
p
¼
0.30 and
p
¼
0.45.
Moreover, our conclusion suggests that we can obtain the results of information
diffusion and dissipative effect through further investigation into information
management and malware infection in information security.
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