a34e0ba3-0258-46e5-9ffa-ba6f0c6058e520250130065040452wseas:wseasmdt@crossref.orgMDT DepositWSEAS TRANSACTIONS ON COMPUTER RESEARCH2415-15211991-875510.37394/232018http://wseas.org/wseas/cms.action?id=13372110202511020251310.37394/232018.2025.13https://wseas.com/journals/cr/2025.phpYangZhangZhengzhou Shengda University, Zhengzhou 451191, CHINAConventional 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.1302025130202514815615https://wseas.com/journals/cr/2025/a305118-307.pdf10.37394/232018.2025.13.15https://wseas.com/journals/cr/2025/a305118-307.pdfLiu Y, Fan C S, Liu P X.Research on Digital Media Intelligent Art Creation Based on the Fusion of Virtual Reality and Semantic Features. Journal of information science and engineering: JISE, Vol. 39, No. 1, 2023, pp. 55-66. 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