Refined push method of marketing data based on social trust network Online publication date: Wed, 21-Feb-2024
by Xiaohuan Ning
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 30, No. 1, 2024
Abstract: In order to reduce the push error of marketing data and improve user satisfaction, a refined push method of marketing databased on social trust networks is proposed. Firstly, crawler technology is used to collect user online browsing data from server logs. Secondly, a social trust network graph is constructed to calculate the cognitive trust strength and interactive trust strength of users. Finally, based on the trust strength calculation results, Pearson correlation coefficient is used to calculate the user's rating similarity, and a marketing data refinement push function is constructed based on the rating similarity to complete the refinement push of marketing data. The experimental results show that compared with existing push methods, the root mean square error and average absolute error of the proposed method are significantly reduced, and user satisfaction is significantly improved, with user satisfaction basically maintained at over 90%.
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