通过复杂的网络在线音乐文化的沟通和结构来分析观众的心理健康
Enhui Li1, Xinyi Liang2, Zixi Wang3
1College of Music and Dance, Guangzhou University, Guangzhou, 510006, P. R. China.
Scientific reports
|January 8, 2026
概括
本研究引入了一种新的基于代理的非线性方程 (ABM-NE) 模型,用于在线音乐交流,增强传播稳定性和用户匹配,以保护文化和心理健康.
科学领域:
- 复杂的网络 复杂的网络
- 计算社会科学 计算社会科学
- 数字文化研究 数字文化研究
背景情况:
- 在线音乐交流涉及复杂的传播动态.
- 传统模型在用户多样性和传播稳定性方面扎.
- 个性化体验对于创作者,平台和用户来说至关重要.
研究的目的:
- 开发一种分析在线音乐文化传播的新型模型.
- 提高信息传播的稳定性和效率.
- 改善内容与受众的匹配,并支持数字文化遗产.
主要方法:
- 开发了一种混合的基于代理的模拟与非线性方程 (ABM-NE) 模型.
- 使用ABM模拟的多源传播行为.
- 分析了使用NE的节点状态演变和动态重量调整.
主要成果:
- 该ABM-NE模型显示了比传统模型 (BA,Holme-Kim) 更稳定的节点密度波动.
- 用户反显著增强了社会影响力,达到0.91.
- 高度的社会影响力,匹配程度和整合导致了高效的传播 (0.77-0.8).
结论:
- 在复杂的网络环境中,ABM-NE模型提供了卓越的稳定性和适应性.
- 它可以准确预测传播效应,并改善内容与受众的匹配.
- 该模型支持传统音乐的数字继承,并增强观众的心理健康.
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