Big Data Analysis of Music Influencing Factors Based on Complex Network

Rui Zhu, Yuanyuan Jiao, Liang Bai, Nanjun Li

2022

Abstract

Music plays an important role in human society. This paper attempts to explore the law of music development through the music style of artists over the years, the works created and the mutual influence between artists. Firstly, this paper adopts node aggregation algorithm to simplify the complex network of artists of different ages and genres into a simple sub-network. Then, based on the cosine distance, this paper analyzed musical characteristics of artists so as to work out the similarity degree between them. Finally, this paper combines the development of society and technology to comprehensively analyze the law of the development of music, and draws the conclusion that different music genres have different influences in different ages. Major social changes and major scientific and technological development related to music will also have a great impact on the development of music.

Paper Citation

in Harvard Style

Zhu R., Jiao Y., Bai L. and Li N. (2022). Big Data Analysis of Music Influencing Factors Based on Complex Network. In Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME; ISBN 978-989-758-630-9, SciTePress, pages 290-294. DOI: 10.5220/0011910700003613

in Bibtex Style

@conference{nmdme22,
author={Rui Zhu and Yuanyuan Jiao and Liang Bai and Nanjun Li},
title={Big Data Analysis of Music Influencing Factors Based on Complex Network},
booktitle={Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME},
year={2022},
pages={290-294},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011910700003613},
isbn={978-989-758-630-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME
TI - Big Data Analysis of Music Influencing Factors Based on Complex Network
SN - 978-989-758-630-9
AU - Zhu R.
AU - Jiao Y.
AU - Bai L.
AU - Li N.
PY - 2022
SP - 290
EP - 294
DO - 10.5220/0011910700003613
PB - SciTePress