The Exploration of Information Management of News Materials in the New Media Era

Abstract

With the development of new media technologies, news materials have become highly digitalized, multimodal, and cross-platform, exhibiting complexity and dynamism in their generation, storage, and dissemination. The materials include text, images, audio, video, and interactive data, accompanied by geographical, temporal, and user behavior information, resulting in data structures that are nonlinear, multilevel, and semantically multidimensional. Based on artificial intelligence, cloud computing, and big data technologies, this paper explores methods for the multisource collection, intelligent storage, cross-modal classification, tagging management, content correlation, and knowledge mining of news materials, and analyzes their applications in information retrieval, dynamic monitoring, and visual decision-making. The study shows that constructing an intelligent, dynamic, and scalable management system can significantly improve material processing efficiency, information integration capability, and knowledge utilization value, providing technical support and innovative pathways for news information management in the new media environment.