A red culture content production and recommendation system based on artificial intelligence

Abstract

This study aims to explore an artificial intelligence (AI) based red culture content production and recommendation system, and analyze how the system can effectively improve users’ contact frequency, cognitive depth, satisfaction and participation in red culture content, as well as promote users’ positive emotional responses. Through regression analysis and correlation analysis of 759 valid questionnaires, this study verified four core research hypotheses: AI recommendation system can significantly increase users’ exposure to red cultural content; enhance the depth of users’ cognition of red culture; increase user satisfaction and engagement; and eliciting positive emotional responses from users. The results show that personalized recommendation mechanisms play a key role in improving user experience, while strengthening the emotional resonance of content can significantly improve user engagement and communication willingness. In addition, this study also puts forward suggestions such as optimizing the algorithm of the recommendation system, multi-channel operation, and establishing a continuous monitoring and evaluation mechanism, so as to further improve the intelligent communication effect of red cultural content. This study provides theoretical and empirical support for the intelligent dissemination of red culture, and has important practical significance and academic value for the use of AI technology to promote red culture.