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