Balanced and Unbalanced Triangle Count in Signed Networks

被引:3
作者
Arya, Aikta [1 ]
Pandey, Pradumn Kumar [1 ]
Saxena, Akrati [2 ]
机构
[1] Indian Inst Technol, Dept Comp Sci & Engn, Roorkee 247667, Uttarakhand, India
[2] Leiden Univ, Leiden Inst Adv Comp Sci, NL-2333 CA Leiden, Netherlands
关键词
Complex networks; incremental approach; signed networks; triangle counting;
D O I
10.1109/TKDE.2023.3272657
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Triangle count is a frequently used network statistic, possessing high computational cost. Moreover, this task gets even more complex in the case of signed networks which consist of unbalanced and balanced triangles. In this work, we propose a fast I ncremental T riangle C ounting (ITC) algorithm for counting all types of triangles, including balanced and unbalanced. The proposed algorithm updates the count of different types of triangles for newly added nodes and edges only instead of recalculating the same triangle multiple times for the entire network repeatedly. Thus, the proposed ITC algorithm also works for dynamic networks. The experimental results show that the proposed method is practically efficient having run time complexity of O(mk(max)) , where m represents the number of edges and k(max) represents the maximum degree of the given signed network.
引用
收藏
页码:12491 / 12496
页数:6
相关论文
共 42 条
  • [1] Corona product of signed graphs and its application to modeling signed networks
    Adhikari, Bibhas
    Singh, Amrik
    Yadav, Sandeep Kumar
    [J]. DISCRETE MATHEMATICS ALGORITHMS AND APPLICATIONS, 2023, 15 (01)
  • [2] [Anonymous], 2016, INT AAAI C WEB SOCIA
  • [3] Sampling methods and estimation of triangle count distributions in large networks
    Antunes, Nelson
    Guo, Tianjian
    Pipiras, Vladas
    [J]. NETWORK SCIENCE, 2021, 9 : S134 - S156
  • [4] Detecting coalitions by optimally partitioning signed networks of political collaboration
    Aref, Samin
    Neal, Zachary
    [J]. SCIENTIFIC REPORTS, 2020, 10 (01)
  • [5] PATRIC: A Parallel Algorithm for Counting Triangles in Massive Networks
    Arifuzzaman, Shaikh
    Khan, Maleq
    Marathe, Madhav
    [J]. PROCEEDINGS OF THE 22ND ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM'13), 2013, : 529 - 538
  • [6] Structural Reconstruction of Signed Social Networks
    Arya, Aikta
    Pandey, Pradumn Kumar
    [J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2023, 10 (05) : 2599 - 2612
  • [7] Becchetti L., 2008, P 14 ACM SIGKDD INT, P16, DOI [DOI 10.1145/1401890.1401898, 10.1145/1401890.1401898]
  • [8] Efficient Algorithms for Large-Scale Local Triangle Counting
    Becchetti, Luca
    Boldi, Paolo
    Castillo, Carlos
    Gionis, Aristides
    [J]. ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA, 2010, 4 (03)
  • [9] How to Count Triangles, without Seeing the Whole Graph
    Bera, Suman K.
    Seshadhri, C.
    [J]. KDD '20: PROCEEDINGS OF THE 26TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING, 2020, : 306 - 316
  • [10] Discovering Polarized Communities in Signed Networks
    Bonchi, Francesco
    Galimberti, Edoardo
    Gionis, Aristides
    Ordozgoiti, Bruno
    Ruffo, Giancarlo
    [J]. PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM '19), 2019, : 961 - 970