Title: Online financial product marketing information push method based on social relationship network analysis

Authors: Zihan Gao

Addresses: Faculty of Business and Economics, The University of Melbourne, Melbourne, 3052, Australia

Abstract: The research on online financial product marketing information push is of great significance for improving the efficiency of financial institutions, optimising product design, and promoting financial technology innovation and digital transformation. In order to solve the problems existing in current methods, an online financial product marketing information push method based on social relationship network analysis is proposed. This method uses social network to analyse and calculate the influence of user relationship, and combines with two-way gated recurrent unit (GRU) neural network to extract user interest. Push online financial product marketing information based on user interests and multi-Markov chain. Experimental results show that the proposed method performs well in accuracy, push time and user retention rate. Therefore, this method has the characteristics of high precision and high efficiency.

Keywords: social relationship network analysis; online financial product; marketing information push; two-way GRU neural network; multi-Markov chain.

DOI: 10.1504/IJNVO.2025.145370

International Journal of Networking and Virtual Organisations, 2025 Vol.32 No.1/2/3/4, pp.70 - 85

Received: 20 May 2024
Accepted: 27 Aug 2024
Published online: 31 Mar 2025 *

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