引用动态的分数随机模型与内存和波动性
1National Graduate Institute for Policy Studies, Embassy of Japan in the United States of America, Washington, DC, USA and SciREX Center, Tokyo, Japan.
Physical review. E
|November 18, 2025
概括
科学中的引用动态是由注意力的新模型解释的. 这个模型通过考虑记忆效应和随机波动来解决日志常态和权力定律引用分布之间的矛盾.
科学领域:
- 网络理论 网络理论
- 科学的科学科学科学的科学.
- 图书统计学 图书统计学
背景情况:
- 引用网络显示了日志正常分布,但在高引用制度中也显示了权力法行为,这是一个矛盾.
- 了解引用动态对于网络理论和科学科学至关重要.
研究的目的:
- 为了解决引文分配法律中明显的矛盾.
- 引入一个统一的框架来理解引文动态.
主要方法:
- 开发了使用分数布朗运动的潜在注意力的随机模型.
- 分析了日志引用数量随时间的变异.
- 模拟了注意力动态,并分析了arXiv电子印刷品.
主要成果:
- 确定了日志引用数量变异与出版以来的时间 (t^H) 之间的权力法关系.
- 证明反持久注意力 (H<1/2) 导致日志正常分布,而持久注意力 (H>1/2) 导致功率定律.
- 对arXiv数据的实证分析显示了反持续的注意力 (H≈0.13).
结论:
- 该研究提供了一个统一的框架,将记忆效应和注意力波动与引用网络演变联系起来.
- 这些发现为引用分布中的日志-正常-乘法矛盾提供了解决方案.
- 该模型促进了对科学和其他领域的集体注意力动态的理解.
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