Research on Weibo marketing advertising push method based on social network data mining

被引：0

作者：

Zhang, Yanyan ^{[1
]}

机构：

[1] Anqing Vocational and Technical College, Anhui, Anqing

来源：

International Journal of Electronic Business | 2024年 / 19卷 / 04期

关键词：

advertising push; attention mechanism; data mining; graph clustering; social network data; Weibo marketing advertising;

D O I：

10.1504/IJEB.2024.141855

中图分类号：

学科分类号：

摘要：

The current advertising push methods have low accuracy and poor advertising conversion effects. Therefore, a Weibo marketing advertising push method based on social network data mining is studied. Firstly, establish a social network graph and use graph clustering algorithm to mine the association relationships of users in the network. Secondly, through sparsisation processing, the association between nodes in the social network graph is excavated. Then, evaluate the tightness between user preferences and other nodes in the social network, and use the TF-IDF algorithm to extract user interest features. Finally, an attention mechanism is introduced to improve the deep learning model, which matches user interests with advertising domain features and outputs push results. The experimental results show that the push accuracy of this method is higher than 95%, with a maximum advertising click through rate of 82.7% and a maximum advertising conversion rate of 60.7%. Copyright © 2024 Inderscience Enterprises Ltd.

引用

页码：393 / 406

页数：13

共 20 条

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