Abstract

When analyzing social networks, graph data structures are often used. Such graphs may have a complex structure that makes their operational analysis difficult or even impossible. This paper discusses the key problems that researchers face in the field of processing big graphs in that particular area. The paper proposes a reference architecture for storage, analysis and visualization of social network graphs, as well as a big graph process Pipeline. Based on this pipeline it is possible to develop a tool that will be able to filter, aggregate and process in parallel big graphs of social networks, and at the same time take into account its structure. The paper includes the implementation of that pipeline using the OrientDB graph database for storage, parallel processing for graph measures calculation and visualization of big graphs using D3. The paper also includes the conducted experiments based on the calculation of betweenness centrality of some graphs collected from the VKontakte social net.

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