Organization of data collection and processing of sociodynamic processes with possible self-organization and memory availability and analysis of observed characteristics of their time series
Abstract
he article discusses the development of specialized software for collecting, processing and storing data from sociodynamic processes (changing the emotional color of user comments on published news in online media, and electoral campaigns of the US presidential elections in 2012 and 2016). It has been shown that for its creation it is possible to use the pipeline principle with the implementation of a microservice architecture, and for storing data, taking into account their specifics and origin, the use of graph databases is preferable. Based on the collected data, time series of observed processes were obtained. Their R/S analysis showed that they had antipersistance. A study of the dependence of the mathematical expectation, variance and excess of the amplitudes of deviations of series levels from the dimensions of the amplitude calculation time interval ("sliding window") showed that for the mathematical expectation there is a root dependence of fractional degree; for dispersion - the power law with a fractional indicator greater than 1.5; and the behavior of the excess shows the presence of the so-called "heavy tails," its magnitude is significantly greater than that of the normal distribution. The obtained results indicate that the time series of the processes under consideration have unsteady, non-locality, both in time (have memory) and state (show self-organization).
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