Topic Selection and Host Strategy of Cross-Cultural TV Talk Shows with the Aid of a Fuzzy Decision Support System

Television talk shows depend on selecting topics that captivate global audiences while respecting cultural diversity and ensuring relevance.This paper introduces a novel Combined Derivative Assessment Method (CDAM) supported by a Fuzzy Decision Support System (FDSS) to enhance topic selection and host strategies for cross-cultural TV programs.The method systematically evaluates decision-making factors to address challenges such as cultural adaptability, audience engagement, and relevance.The FDSS dynamically uses realtime feedback and external datasets to refine strategies, ensuring content aligns with diverse audience preferences.The proposed approach significantly improves engagement metrics, achieving a 20% increase in benchmarking performance by mitigating low audience retention and enhancing inclusivity.Validation through comprehensive performance analysis demonstrates the method's ability to optimize program effectiveness across various cultural settings.This research offers a robust solution for designing engaging and culturally sensitive TV content by integrating audience-centric decision frameworks.