计算机与现代化

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政府公文收发记录的可视网络分析

  

  1. 1.山西农业大学文理学院,山西太谷030801;
    2.中航锂电(洛阳)有限公司,河南洛阳471000;
    3.机械工业第六设计研究院有限公司市场运行部,河南郑州450007
  • 收稿日期:2014-03-06 出版日期:2014-05-28 发布日期:2014-05-30
  • 作者简介:樊超(1984-),男,山西太谷人,山西农业大学文理学院讲师,博士,研究方向:人类行为动力学,社会网络,数据挖掘; 王重玺(1984-),男,中航锂电(洛阳)有限公司初级经济师,硕士,研究方向:生产管理,效率提升,生产多要素关联度分析; 高鲁彬(1985-),男,机械工业第六设计研究院有限公司市场运行部工程师,硕士,研究方向:工业工程,质量控制。
  • 基金资助:
    山西农业大学科技创新基金资助项目(201208)

Visibility Network Analysis on Official Documents Distribution  Records

  1. 1. College of Arts and Sciences, Shanxi Agricultural University, Taigu 030801, China;
    2. Luoyang Branch of China Aviation Lithium Battery Co. Ltd., Luoyang 471000, China;
    3. Market Operation Department, SIPPR Engineering Group Co. Ltd., Zhengzhou 450007, China
  • Received:2014-03-06 Online:2014-05-28 Published:2014-05-30

摘要: 传统的人类动力学分析大多从单一的时间间隔角度入手,不能全面反映人类行为的标度规律。对此,以政府公文的真实收发记录为研究对象,以时间序列和复杂网络为工具,分析人类行为的时间间隔特征和数量特征。首先分析收文的时间间隔分布,发现其累计分布表现为幂律形式。其次采用重标极差法对收文数量的时间序列进行分析,得到Hurst指数和非周期循环长度,显示该时间序列具有分形特征。然后用可视图和水平可视图方法将该时间序列转换为复杂网络,网络具有无标度特征、小世界效应和等级结构,说明不同时间段内的人类行为密切关联。最后讨论可视图和水平可视图这两种算法的异同点和适用范围。

关键词: 人类动力学, 政府公文, 复杂网络, 时间序列分析, 可视图

Abstract: Traditional research methods on human dynamics most focus on a single perspective of inter-event time, which cannot fully reflect the scaling law of human behavior. In this paper, inter-event time and amount of human behaviors are investigated based on the records of official documents distribution by means of time series and complex network analysis. Firstly, the inter-event time distribution of each document is analyzed and We find that the cumulative pattern follows power-law distribution. Then, time series is constructed with the amount of official documents. The values of Hurst exponent and length of non-periodic cycle calculated through rescaled range analysis indicate that the time series of human behaviors are fractal with long-range dependence. After that, the time series is converted into complex networks by the visibility and horizontal visibility algorithm. The topological properties of the networks such as scale-free property, small-world effect and hierarchical structure imply that there is a close relationship among the numbers of repetitious behaviors during different periods of time. Finally, the similarities, differences and applicability of both visibility algorithms are discussed.

Key words: human dynamics, official documents, complex networks, time series analysis, visibility graph

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