WSEAS Transactions on Computer Research
Print ISSN: 1991-8755, E-ISSN: 2415-1521
Volume 13, 2025
A Semi-Supervised Learning-based Method for Information Dissemination in Online Fusion Media
Author:
Abstract: Conventional information dissemination methods of online media mainly use the Susceptible Infective Removal model to describe the transformation relationship of information dissemination, which is easily affected by false delay stabilization, resulting in a low dissemination influence index. To solve the above problems, this paper proposes an information dissemination method of online media based on semi-supervised learning. That is to locate the source of network media information dissemination and use semi-supervised learning to design the network media information dissemination algorithm, thus realizing the network media information dissemination. The experimental results show that the designed semi-supervised learning communication method of network financial media information has a high communication influence index, good communication effect, high efficiency, and certain application value, and has made certain contributions to improving the comprehensive quality of network financial media information communication.
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Keywords: Semi-supervised learning, Web, Integrated media, Information, Dissemination, Communication impact index, Information propagation algorithm
Pages: 148-156
DOI: 10.37394/232018.2025.13.15