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Interactive environment for visualization and analysis of large complex networks using affective state of the user


S.V. Kovalchuk – Ph.D. (Eng.), Senior Research Scientist, National Research University of Information Technologies, Mechanics and Optics. E-mail:
A.A. Bezgodov – Ph.D. (Eng.), Senior Research Scientist, National Research University of Information Technologies, Mechanics and Optics. E-mail:
D.M. Terekhov – Student, National Research University of Information Technologies, Mechanics and Optics. E-mail:
A.V. Boukhanovsky – Ph.D. (Eng.), Professor, National Research University of Information Technologies, Mechanics and Optics. E-mail:

Contemporary technological approaches to human-computer interaction (including virtual and augmented reality) put strong attention on the user’s reaction which includes changes in affective state of the user. The researches in the area of affective computing are especially important within tasks of decision support systems’ (DSS) development for complex objects control in extreme conditions. This is caused by the fact that the affective state of decision maker can have an influence on the decision correctness. On the other hand, the tracking of affective state during the visual exploration of data can allow identifying and analyzing the most important objects in an automatic way, that is important in case of large arrays analysis (thus the solution can be applied within BigData paradigm). The development of proposed approach is related to the development concept of augmented cognition, which is focused on the new ways of human-computer symbiosis within complex data analysis. Usually the DSS development depends on particular problem domain. Still the usage of affective computing technology can be developed in more general way within interactive environments and platforms, which define basic human-computer interaction procedures. Within the presented work the approach to development of interactive environment for large data arrays analysis is considered. Complex network analysis task is taken as demo application example for this environment. The complex model of the user within interactive environment is proposed taking into account the affective state of the user. To estimate the affective state special hardware (Brain-Computer Interface – BCI) can be used. Additionally a set of information sources is used to estimate user’s characteristics. This allows estimating psychological, sociological and other factors which have influence on the user sate. The model is implemented within experimental version of interactive virtual environment, which was developed for analysis and interpretation of complex networks. Complex networks are graphs with huge amount of edges and vertices. This allows considering the task within the paradigm of BigData. Moreover large number of elements within the network enables statistical methods to interconnect macro- and micro parameters of the network. The developed virtual environment was tested using the task of visual layout of complex contact network (including different social groups) during the process of infection spread. Proposed approach extends the basic applications of virtual and augmented reality technologies. The key direction of the approach development is usage within DSS applications and expert knowledge acquisition through the visual analysis of complex data from different problem domains.

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