Power-Law of Node Degree Distribution and Information Diffusion Process 


Vol. 44,  No. 10, pp. 1866-1877, Oct.  2019
10.7840/kics.2019.44.10.1866


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  Abstract

In this study it is investigated that how both network type and structural characteristics affect dynamic information diffusion of network through simulation. For this purpose we generated various kinds of networks using network generation model, which can well generate various types of networks(scale-free, small-world and random network) and represent various topological characteristics. For information diffusion simulation linear threshold model is used. It is found out that the most important factor which affects the information diffusion is power-law of node degree, which enables the existence of super-hub node, not clustering coefficient. So, we can also see that the information diffusion of small-world network, which has super-hub node due to power-law of node degree distribution, is fast compared to other networks. It is also found out that for the small-world and scale-free networks initial node selection based on node degree provide fast information diffusion compared to random node selection.

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  Cite this article

[IEEE Style]

K. Lee and J. Lee, "Power-Law of Node Degree Distribution and Information Diffusion Process," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 10, pp. 1866-1877, 2019. DOI: 10.7840/kics.2019.44.10.1866.

[ACM Style]

Kang-won Lee and Ji-sang Lee. 2019. Power-Law of Node Degree Distribution and Information Diffusion Process. The Journal of Korean Institute of Communications and Information Sciences, 44, 10, (2019), 1866-1877. DOI: 10.7840/kics.2019.44.10.1866.

[KICS Style]

Kang-won Lee and Ji-sang Lee, "Power-Law of Node Degree Distribution and Information Diffusion Process," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 10, pp. 1866-1877, 10. 2019. (https://doi.org/10.7840/kics.2019.44.10.1866)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880