This study mainly focused on the dynamic self-similar kc-center network as a result of information distribution through social networks. Individual attraction with various preferences was characterized in the model as a result of reciprocal attraction among individuals and human multi-attribute. Additionally, the model incorporated the community network structure and network evolution mechanism, and a dynamic self-similar kc-center network generation model was presented. Compared with the classical scale-free network generation algorithm, the generated network embodied not only the characteristics of the small-world and scale-free, but also the characteristics of dynamic self-similar kc-center network. The experimental results were verified by comparing the real data with the experimental data. The results showed that there are dynamic self-similar kc-center networks and their internal network relationship dynamics in the micro scale, meso scale and global perspective based on information dissemination.
WANG Li1 (李树勋), ZHANG Xuyi2 (沈珩云), YAO Yabing3 (刘斌才),HU Yinggang4*(胡迎港)
. Dynamic Self-Similar kc-Center Network Based on Information
Dissemination[J]. Journal of Shanghai Jiaotong University(Science), 2024
, 29(3)
: 480
-491
.
DOI: 10.1007/s12204-022-2559-6
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