微博的标签使用时间序列中的规模依赖力法属性
Jiwei J Jiang1, Kenta Yamada2, Hideki Takayasu1,3
1School of Computing, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8502, Japan.
Scientific reports
|December 15, 2023
概括
社交媒体的标签使用遵循一个粗尾分布,其权力定律指数取决于标签大小. 我们的模型解释了这种以大小为依赖的现象,为科学领域的脂肪尾分布提供了洞察力.
科学领域:
- 社交媒体分析.
- 网络科学 网络科学
- 统计物理学的统计物理.
背景情况:
- 在社交媒体上使用hashtag通常会表现出复杂的统计属性.
- 了解这些分布的基本机制对于各种应用至关重要.
研究的目的:
- 分析标签使用时间序列的统计属性.
- 开发一个理论模型来解释观察到的大小依赖的hashtags的脂肪尾分布.
主要方法:
- 对社交媒体标签数据的时间序列分析.
- 统计分析以确定权力法指数及其依赖于标签大小.
- 开发和数值模拟一个通用的随机乘法过程模型.
主要成果:
- 标签使用分布的特点是脂肪尾分布.
- 标签增长率分布与它们的使用规模之间存在明显的依赖.
- 拟议的模型成功地复制了观察到的大小依赖性质.
结论:
- 这项研究提供了一个理论解释,以大小为依赖的hashtag使用的脂肪尾分布.
- 一般的随机乘法过程模型为理解不同科学领域中类似现象提供了一个框架.
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