Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

New Media Public Relations Strategy Model Based on Support Vector Machine Algorithm

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  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322694,
        author={Jialin  Li},
        title={New Media Public Relations Strategy Model Based on Support Vector Machine Algorithm},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={support vector machine algorithm; new media; public relations},
        doi={10.4108/eai.17-6-2022.2322694}
    }
    
  • Jialin Li
    Year: 2022
    New Media Public Relations Strategy Model Based on Support Vector Machine Algorithm
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322694
Jialin Li1,*
  • 1: Vanderbilt University
*Contact email: 790693032@qq.com

Abstract

The rise of new media is the result of worldwide scientific and technological development and innovation. The public relations of new media are deeply influenced by scientific and technological innovation, and the focus of public relations has gone through a process of change from management to service to relationship. In the new media era, interaction has increasingly become the focus of attention to promote and improve the quality of public relations. In this paper, the concept of support vector machine is given first, and the basic principle and research status of SVM technology are described in detail. The method of vector machine algorithm for multi-pattern classification is studied, and it is found that too many comparisons are the main reason for the large amount of calculation of this method. Through theoretical analysis and experimental results of data classification, it is shown that compared with the traditional classifier, the new method can significantly reduce the number of machine training and recognition and improve the algorithm running speed without affecting the classification accuracy. Break through the paradigm crisis that the public relations discipline is currently facing and meet its theoretical innovation needs.