Big Data-Driven Ecosystem Integration in the Film and Television Industry

This study developed a big data-driven information resource management framework to integrate creation, production, distribution, and consumption across the global film and television value chain. This research addressed the need to break down data silos, adapt for cross-cultural content, and balance technological efficiency with artistic autonomy. The framework was built by combining artificial intelligence tools (bidirectional encoder representations from transformers and latent Dirichlet allocation), blockchain-based alliance chains, and cultural label conversion rules; these were then validated through controlled experiments and multi-market testing. Results showed higher audience retention, more successful cross-cultural performance, faster production cycles, and reduced levels of disputes. The findings suggested that information resource management optimized data governance, enhanced cultural adaptability, and improved industrial efficiency, thereby offering a scalable model for sustainable digital transformation in the media industry.