Analysis of the Correlation between Algorithmic Recommendation Logic and Audience Acceptance in Personalized Precision Push Notifications

DOI: https://doi.org/10.62517/jnme.202610213

Author(s)

Yibo Zhao

Affiliation(s)

School of Journalism and Communication,Communication University of China, Nanjing, Nanjing, China

Abstract

This article focuses on the field of personalized and precise push. It deeply analyzes the correlation between the algorithm recommendation logic and the audience's acceptance. By exploring the constituent elements, operation mechanism of the algorithm recommendation logic, and its impact on the audience's information reception environment, combined with the formation process, influencing factors, and internal psychological mechanisms of audience acceptance, it reveals the complex relationship of interaction between the two. The research finds that the algorithm recommendation logic not only improves the efficiency of information matching but also has negative impacts on audience acceptance due to issues such as information cocoons and algorithm biases; while audience acceptance, in turn, affects the optimization and adjustment of the algorithm recommendation logic. Based on this, strategies are proposed to promote the positive interaction between the two in aspects such as algorithm design, user rights protection, and industry regulation, aiming to provide theoretical support and practical guidance for the healthy development of the personalized and precise push field.

Keywords

Personalized Precise Push; Algorithm Recommendation Logic; Audience Acceptance; Relevance

References

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