Research on Multi-Modal Content Co-Governance Strategies in New Media Communication

This paper proposes a multi-level heterogeneous collaborative governance framework to solve the complexity, inefficiency, and accountability gaps in new media multimodal content management, as traditional single-modal/single-platform governance cannot adapt to the rapid convergence and cross-platform spread of text, images, videos, and audio. The framework integrates three collaborative dimensions: cross-modal intelligent detection to break single-modal limits; clear responsibility allocation across platforms, departments, and human-AI teams to resolve accountability ambiguities; and dynamic cross-platform feedback loops for real-time coordination. Empirical analyses show it outperforms traditional models. However, “multi-governance” faces challenges such as data silos, insufficient cross-platform standardization, and algorithmic opacity. Bridging theory and practice, it provides an actionable multi-governance tool for regulators, platforms, and tech providers, contributing to a more secure, efficient, and sustainable new media ecosystem.