A method to improve the time of computing betweenness centrality in social network graph


  • Nguyen Xuan Dung Hanoi Open University, B101 Nguyen Hien Str., Hai Ba Trung Dist., Ha Noi, Viet Nam
  • Doan Van Ban Viet Nam Academy of Science and Technology, 18 Hoang Quoc Viet, Cau Giay Dist., Ha Noi, Viet Nam
  • Do Thi Bich Ngoc Posts and Telecommunications Institute of Technology, 122 Hoang Quoc Viet Str., Cau Giay Dist., Ha Noi, Viet Nam




Betweenness centrality, mining graph data, analyzing social network


The Betweenness centrality is an important metric in the graph theory and can be applied in the analyzing social network. The main researches about Betweenness centrality often focus on reducing the complexity. Nowadays, the number of users in the social networks is huge. Thus, improving the computing time of Betweenness centrality to apply in the social network is neccessary. In this paper, we propose the algorithm of computing Betweenness centrality by reduce the similar nodes in the graph in order to reducing computing time. Our experiments with graph networks result shows that the computing time of the proposed algorithm is less than Brandes algorithm. The proposed algorithm is compared with the Brandes algorithm [3] in term of execution time.


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How to Cite

N. X. Dung, D. V. Ban, and D. T. B. Ngoc, “A method to improve the time of computing betweenness centrality in social network graph”, Vietnam J. Sci. Technol., vol. 57, no. 3, pp. 344–355, Jun. 2019.



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