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.
王丽1，张旭毅2，姚亚兵3，尉雪龙4
. 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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