Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

August 16, 2023


Pages


DOI

Article

The use of new media technology in the creation of media animation under the threshold of big data

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Authors

Ping Guan Affiliation:
College of Art and Design, Fuzhou University of International Studies and Trade, Fuzhou, Fujian, 350202, China.


Abstract

This paper first introduces the support vector machine mining algorithm to find the optimal linearly bounded hyperplane utilizing a nonlinear transformation. Then the algorithm’s comparison criterion is introduced, and its performance is evaluated in terms of accuracy and other aspects. Finally, the support vector machine mining algorithm is used to mine and analyze the problems of traditional animation and the impact of new media technology on the creation of media animation. Among the existing problems, the most important one is that 67.9% of people think the animation content has no connotation and is boring. 7.8% of people think that the technology is not up to the standard and the use of new technology is lacking, and 55% think that the theme is old and repetitive. In the influence of new media technology on media animation creation, 67% think new media technology makes animation themes diversified, 73% think new media technology makes animation content young and theme civilians grounded. 79% think new media technology keeps animation creation up with the times, and connotation and creativity are improved. New media technology makes media animation’s connotation theme sublimated, but it also should reflect on its shortcomings in time with the development of the times.


Keywords

Big data perspective, New media technology, Media animation, Support vector machine, Data mining, 76S05


Citation

Guan, P. (2023). The use of new media technology in the creation of media animation under the threshold of big data. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00190

Published by: Engineering Journals

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