Matrix: SNAP/cit-HepPh

Description: Arxiv High Energy Physics paper citation network

SNAP/cit-HepPh graph SNAP/cit-HepPh graph
(bipartite graph drawing) (graph drawing of A+A')

scc of SNAP/cit-HepPh

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  • download as a MATLAB mat-file, file size: 1 MB. Use UFget(2292) or UFget('SNAP/cit-HepPh') in MATLAB.
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    Matrix properties
    number of rows34,546
    number of columns34,546
    # strongly connected comp.21,608
    explicit zero entries0
    nonzero pattern symmetry 0%
    numeric value symmetry 0%
    Cholesky candidate?no
    positive definite?no

    authorJ. Gehrke, P. Ginsparg, J. Kleinberg
    editorJ. Leskovec
    kinddirected graph
    2D/3D problem?no

    Additional fieldssize and type
    nodenamefull 34546-by-1


    Networks from SNAP (Stanford Network Analysis Platform) Network Data Sets,      
    Jure Leskovec                          
    email jure at                                                   
    High-energy physics citation network                                            
    Dataset information                                                             
    Arxiv HEP-PH (high energy physics phenomenology ) citation graph is from the    
    e-print arXiv and covers all the citations within a dataset of 34,546 papers    
    with 421,578 edges. If a paper i cites paper j, the graph contains a directed   
    edge from i to j. If a paper cites, or is cited by, a paper outside the         
    dataset, the graph does not contain any information about this.                 
    The data covers papers in the period from January 1993 to April 2003 (124       
    months). It begins within a few months of the inception of the arXiv, and thus  
    represents essentially the complete history of its HEP-PH section.              
    The data was originally released as a part of 2003 KDD Cup.                     
    Dataset statistics                                                              
    Nodes   34546                                                                   
    Edges   421578                                                                  
    Nodes in largest WCC    34401 (0.996)                                           
    Edges in largest WCC    421485 (1.000)                                          
    Nodes in largest SCC    12711 (0.368)                                           
    Edges in largest SCC    139981 (0.332)                                          
    Average clustering coefficient  0.2962                                          
    Number of triangles     1276868                                                 
    Fraction of closed triangles    0.1457                                          
    Diameter (longest shortest path)    12                                          
    90-percentile effective diameter    5                                           
    Source (citation)                                                               
    J. Leskovec, J. Kleinberg and C. Faloutsos. Graphs over Time: Densification     
    Laws, Shrinking Diameters and Possible Explanations. ACM SIGKDD International   
    Conference on Knowledge Discovery and Data Mining (KDD), 2005.                  
    J. Gehrke, P. Ginsparg, J. M. Kleinberg. Overview of the 2003 KDD Cup. SIGKDD   
    Explorations 5(2): 149-151, 2003.                                               
    File    Description                                                             
    cit-HepPh.txt.gz    Paper citation network of Arxiv High Energy Physics category
    cit-HepPh-dates.txt.gz  Time of nodes (paper submission time to Arxiv)          

    SVD-based statistics:
    null space dimension8,169
    full numerical rank?no
    singular value gap3.44355e+09

    singular values (MAT file):click here
    SVD method used:s = svd (full (A))

    SNAP/cit-HepPh svd

    For a description of the statistics displayed above, click here.

    Maintained by Tim Davis, last updated 12-Mar-2014.
    Matrix pictures by cspy, a MATLAB function in the CSparse package.
    Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.