基于因果模型的社交网络用户购物行为研究

doi:10.12052/gdutxb.190147

Abstract

Abstract: Shopping behaviors in the social network can reflect users’ willingness to meet their material needs and social needs under the influence of social interaction, which is an important research in social network marketing. The traditional analysis of online shopping behavior only focuses on the similarity between users’ behaviors while ignoring the influence of users’ social needs and peer behaviors. For that, the features of users’ shopping behavior are constructed by combining anti-conformity theory and social needs. Secondly, aiming at the incomplete observation of user data in social network, a causal mechanism discovery algorithm for users’ behaviors based on Fast Causal Inference (FCI) is proposed. Finally, the rationality of the causal mechanism of our model is verified based on the experimental analysis and empirical analysis.

Key words: online shopping, social behavior, anti-conformity, FCI algorithm, causal network

CLC Number:

TP301.6

Hao Zhi-feng, Li Yi-ting, Cai Rui-chu, Zeng Yan, Qiao Jie. A Research on Users’ Shopping Behaviors in Social Network Based on Causal Model[J].Journal of Guangdong University of Technology, 2020, 37(03): 1-8.

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