Мальцева Светлана Валентиновна

Nonlinear Dynamical Analysis of Twitter Time Series

2017 · CHAPTER · en

The Demand for the Healthcare Services: the Opportunities of Big Data in Predicting Patient Flow

2017 · CHAPTER · en

Modeling of Microblogging Social Networks: Dynamical System vs. Random Dynamical System

2017 · CHAPTER · en

Building of adequate dynamical models of microblogging social networks is a topical task that is of interest from both theoretical and practical aspects. Experimental and theoretical results of studies related to choice of the adequate model are presented. The choice was made between two models: a nonlinear dynamical system and a nonlinear random dynamical system. By results of the fractal analysis of observable network time series and defining their probability density function it was established that the nonlinear random dynamical system was more adequate than the nonlinear dynamical system. The character of the observable time series was also explored. The possibility that microblogging social networks can be analyzed by means of Tsallis entropy and self-organized criticality is examined.

Моделирование и качественный анализ социальной микроблогинговой сети как динамической системы

2016 · ARTICLE · ru

Представлены результаты качественного анализа социальной сети, базирующейся на принципе микроблогинга. Сетевое взаимодействие аппроксимировалось дифференцируемой нелинейной динамической системой числа отправителей и получателей заметок (без ограничений и с ограничениями). Установлено, что адекватной является динамическая система с учетом «насыщения» и взаимодействий между отправителями и получателями. Получены параметрические условия асимптотической устойчивости и вилообразной бифуркации для условий сетевой динамики.

Investigation into the Regular and Chaotic States of Microblogging Networks as Applied to Social Media Monitoring

2016 · CHAPTER · en

The present paper is devoted to the investigation into the evolutionary dynamics of social microblogging networks. Different network states are considered. Regular and chaotic states of networks are described. A new model of a social microblogging network as a point dissipative system is suggested. Dynamic variables of such system are represented by the variations of tweet/retweet number around the equilibrium values. It is pointed out, that the system is in a condition of an asymptotically stable equilibrium when the intensity values of an external information are small (the number of tweets eventually tends to its equilibrium value). So far as the intensity values of external information do not exceed the critical value, the stable (almost harmonic) oscillations of tweets take place in the system. If the intensity values of external information exceed the critical value, then the chaotic oscillations of tweets are to be observed. A case of Twitter network is examined.

Application of the Nonlinear Oscillations Theory to the Study of Non-equilibrium Financial Market

2016 · ARTICLE · en

The research deals with the construction, implementation and analysis of the model of the non-equilibrium financial market using econophysical approach and the theory of nonlinear oscillations. We used the scaled variation of supply and demand prices and elasticity of these two variables as dynamic variables in the simulation of the non-equilibrium financial market. View of the dynamic variables data was determined based on the strength of econophysical prerequisites using the model of hydrodynamic type. As a result, we found that the non-equilibrium market can be described with a good degree of accuracy with oscillator models with nonlinear rigidity and a self-oscillating system with inertial self-excitation. The most important states of model of oscillation non-equilibrium model of the market were found, including the appearance of chaos and its mechanisms. We have made the calculations of the correlation dimension for the financial time series. The results show that all observed time series have a clearly defined chaotic dynamic nature.

Web 3.0 and Smart Commerce (W3SC 2016) Preface

2016 · CHAPTER · en

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Network Evolution Modeling under Conditions of Change in the Data Exchange Rate

2016 · CHAPTER · en

The present paper is devoted to the research into the topical questions of network evolution modeling considering the constant changes in the data environment as well as the data exchange rate. A two-level approach to the network community analysis based on the division into macro- and micro-levels of monitoring is suggested. Functionality of both levels is described. Suggestions for investigation and modeling of data flows in a network represented by a dynamical system of message senders and recipients are presented.

Investigation into the Regular and Chaotic States of Microblogging Networks as Applied to Social Media Monitoring

2016 · CHAPTER · en

The present paper is devoted to the investigation into the evolutionary dynamics of social microblogging networks. Different network states are considered. Regular and chaotic states of networks are described. A new model of a social microblogging network as a point dissipative system is suggested. Dynamic variables of such system are represented by the variations of tweet/retweet number around the equilibrium values. It is pointed out, that the system is in a condition of an asymptotically stable equilibrium when the intensity values of an external information are small (the number of tweets eventually tends to its equilibrium value). So far as the intensity values of external information do not exceed the critical value, the stable (almost harmonic) oscillations of tweets take place in the system. If the intensity values of external information exceed the critical value, then the chaotic oscillations of tweets are to be observed. A case of Twitter network is examined.

The Nonlinear Differential Dynamics of Interdependent Branches of Industry

2015 · CHAPTER · en

Nonlinear differential dynamic model of the relation between the branches of production was proposed. Mathematically, this model is expressed as a system of first-order ODE. Dynamic variables of the model – the value of the output of each branch of production. Each differential equation of the system includes independent growth and diminution of finished goods; growth and decline of production related to the production of allied industries. Two models were proposed: a model with Malthusian products growth (model with no restrictions on the amount of product), the model with the Verhulst limiting of the growth of output. The equilibrium points of dynamical systems, system stability were determined as well as the qualitative analysis of dynamic systems was made.