Feedback Reception and Narrative Reproduction of New Media Products in New Mainstream Media: A Perspective on Media Convergence Productio

Abstract

Against the backdrop of deepening media convergence, new mainstream media platforms are accelerating their transformation toward intelligence, with algorithmic feedback technologies deeply embedded in content production. However, new media products across different platforms exhibit significant differences in narrative innovation and communication effects. This study adopts semi-structured in-depth interviews with 11 new media practitioners from Chinese mainstream media at various levels, constructing an analytical framework of “feedback integration into production” by integrating media production theory and cybernetic-feedback theory. The findings reveal that algorithmic feedback data enters production through multiple channels and is selectively perceived by creative teams; during interpretation, political orientation requirements, social responsibility considerations, and professional creative concepts intersect with algorithmic logic, forming a hybrid evaluation system; based on complex feedback processing, creative teams make specific framework adjustments in subsequent narrative reproduction. This study reveals the practical logic and power dynamics of “data-human-organization” interaction in new mainstream media content production.