Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 6, Issue 2


Published
on

August 17, 2022


Pages

975-984


DOI

Article

Copyright protection of original online music products based on applied statistical mathematics – take music trade network as an example

Check for updates


Authors

Tao Jiang Affiliation:
Department of Art, West Anhui University, Lu’an, Anhui, China
, Keqing Dai Affiliation:
School of Economics and Management, Anhui Jianzhu University, Hefei, Anhui, China
and Moaiad Khader Affiliation:
Department of Computer Science, College of Arts and Science, Applied Science University, Bahrain


Abstract

With globalization and the rapid evolution of internet, the channels of music communication have become diversified. The communication speed of online music has become faster, and the music-related information is enriched on the internet. However, these positive effects on music communication also increase the complexity of music copyright issues. In face of the great challenges on music copyright issues, this paper takes the online original music works trading platform, namely music trading network as the research object, and uses some mathematical methods, such as statistical theory, power function law and long tail theory, to discuss the copyright protection of the music trading network. Our motivation is to find a way to protect the copyright of original music product so as to stimulate the enthusiasm of musicians, as well as to help find a way to create a healthy original music ecosystem.


Keywords

statistical mathematics, online music, long tail theory, copyright, time stamp


Citation

Jiang, T., Dai, K., & Khader, M. (2021). Copyright protection of original online music products based on applied statistical mathematics – take music trade network as an example. Applied Mathematics and Nonlinear Sciences, 6(2), 975–984. https://doi.org/10.2478/amns.2021.2.00209

Published by: Engineering Journals

Engineering Journals Logo