Research on Maximizing Influence of Blockchain Social Network Based on BCLT Model

Chang Liu, Sheng Bin and Giulio E. Cantarella

Discrete Dynamics in Nature and Society, 2022, vol. 2022, 1-8

Abstract: In the blockchain social network, the traditional influence maximization algorithm has the problem of insufficient accuracy of the influence spread. To solve the above problem, a BCLT model including the characteristics of the blockchain is established based on the linear threshold model. The BC-RIS algorithm is proposed based on the reverse reachable set. The BC-RIS algorithm's influence spread and running time and the traditional algorithm is compared using the real blockchain social network data set. The experimental results show that the BC-RIS algorithm can obtain a larger influence spread range, which is more in line with the influence propagation law of the blockchain social network.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:7335390

DOI: 10.1155/2022/7335390

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