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Physica A Volume 391, Issue 24, 15 December 2012, Pages 6617–6625
In this paper, the fractal characteristic of human behaviors is investigated from the perspective of time series constructed with the amount of library loans. The values of the Hurst exponent and length of non-periodic cycle calculated through rescaled range analysis indicate that the time series of human behaviors and their sub-series are fractal with self-similarity and long-range dependence. Then the time series are converted into complex networks by the visibility algorithm. The topological properties of the networks such as scale-free property and small-world effect imply that there is a close relationship among the numbers of repetitious behaviors performed by people during certain periods of time. Our work implies that there is intrinsic regularity in the human collective repetitious behaviors. The conclusions may be helpful to develop some new approaches to investigate the fractal feature and mechanism of human dynamics, and provide some references for the management and forecast of human collective behaviors.
Keywords文章PDF: PHYSA_13934_proof.pdf
http://www.sciencedirect.com/science/article/pii/S0378437112006231
我们采用的数据是两所图书馆的借阅量,以及借阅的间隔时间。用重标极差法计算了以借阅量为观测值构成的时间序列的Hurst指数和非周期循环长度,发现人类行为具有长期正相关性和持续性,记忆效应对借阅行为有强烈影响,并与时间标度有关。群体用户的分形特征表现较为明显,而个体用户的时间序列中则有一定的波动性;并且不同的用户群之间,以及同一个数据集中的不同用户之间表现出了显著的个体差异。
通过可视算法将人类行为的时间序列和复杂网络结合在一起,计算了由时间序列转化得到的复杂网络的拓扑参数,发现群体用户的网络具有无标度特征、小世界效应和等级结构,而个体用户的网络则只具有以上部分性质。可以认为,人类的重复性行为发生的时间序列中各个观测值之间存在潜在的密切联系,特别是对于日常生活中的某些重要时刻。我们还发现只有部分的个体行为网络具有分形结构和自相似的特征。此外,本文的分析也对于找寻时间序列和复杂网络之间的关系、网络属性之间的关系以及网络分形结构的起源具有一定的借鉴意义。
注:中文内容中部分结论是笔者硕士论文中的一部分,没有写进这篇英文版本中,也欢迎同行批评指正!
《从图书借阅看人类群体和个体行为的动力学机制》,樊超,上海理工大学,2011年。
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