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Title: Optimising news dissemination pathways in the media convergence era: an interactive digital media technology approach

Authors: Yingxi Zhang; Ya Liu; Zhuoya Guo

Addresses: Cheongju University, Cheongju 363170, South Korea ' Faculty of Letters and Journalism and Communication, Sanjiang University, Nanjing 210000, China; Cheongju University, Cheongju 363170, South Korea ' College of Culture and Media, Kaifeng Vocational College of Culture and Arts, Kaifeng 475000, China

Abstract: In the era of media convergence, traditional news dissemination systems confront dual challenges of information entropy overload and diminished user engagement. This research proposes an intelligent propagation path optimisation framework leveraging interactive digital media, which integrates multimodal data perception with dynamic user behaviour feedback to establish a dual-layer reinforcement learning decision model. The methodology comprises three core components: a dynamic user interest quantification model combining temporal attention mechanisms with deep feature extraction, a Q-value iteration mechanism with entropy-constrained adaptive learning rate optimisation, and a multi-objective Pareto-optimal framework balancing coverage and timeliness under resource constraints.

Keywords: interactive digital media; media convergence; dissemination path optimisation; reinforcement learning; information entropy.

DOI: 10.1504/IJICT.2025.147882

International Journal of Information and Communication Technology, 2025 Vol.26 No.29, pp.110 - 126

Received: 02 Jun 2025
Accepted: 16 Jun 2025
Published online: 05 Aug 2025 *