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Social networks analysis by graph
algorithms on the example of the VKontakte social network St.
Petersburg Institute for Informatics and Automation (SPIIRAS) St.
Petersburg, 14 line V.O. , 39, 199178, Russia {kolomeec, chechulin, ivkote}@comsec.spb.ru
Abstract The development of social networks made it possible to form very complex structures of users and their content. As new services are added for users, the number of vertex types and edge types increase in the social network graph. Such structural increase opens up new opportunities for analysis. It becomes possible to obtain information about users, communities or trends by analyzing not the numerical or text information, but the structures that they form. Such structures can give a more accurate picture of the user, the community or the trend. To analyze these graph structures of social networks, one can use the entire arsenal of graph algorithms. In this paper, we consider their practical use in analyzing the growing structures of social networks and their limitations on the example of one of the largest social networks – VKontakte. The paper provides analysis and classification of graph algorithms in the context of social networks, as well as an approach to the analysis of the social network VKontakte using the graph database OrientDB. accurately. Keywords: Social networks analysis, Graph
processing, Network analysis, Graph database +: Corresponding author: Igor Kotenko Journal
of Wireless Mobile Networks, Ubiquitous Computing, and Dependable
Applications (JoWUA) Vol.
10, No. 2, pp.55-75, June 2019 [pdf] Received: April 11, 2019; Accepted: June
15, 2019; Published: June 30, 2019 |