Influencer IP marketing copywriting generation and optimization based on natural language processing
Xueli Zhang, Wenzheng Wang · 2024
To improve the efficiency and personalization of influencer IP marketing copywriting, this paper designs and implements an automated copywriting generation system based on natural language processing (NLP) technology. By constructing the system architecture, integrating NLP models, and optimizing the generation module, it analyzes the entire process of copy creation, management, and display. The results show that the system can effectively enhance copywriting efficiency, reduce the need for manual intervention, and demonstrate strong adaptability and scalability in managing and displaying content across multiple platforms.