%-------------------------------------------------------------------------------
% SuiteSparse Matrix Collection, Tim Davis
% https://sparse.tamu.edu/SNAP/wiki-talk-temporal
% name: SNAP/wiki-talk-temporal
% [SNAP network: wiki-talk temporal network]
% id: 2798
% date: 2017
% author: A. Paranjape, A. R. Benson, and J. Leskovec
% ed: J. Leskovec
% fields: name title A id date author ed kind notes aux
% aux: temporal_edges usernames
% kind: directed temporal multigraph
%-------------------------------------------------------------------------------
% notes:
% SNAP (Stanford Network Analysis Platform) Large Network Dataset Collection,
% Jure Leskovec and Anrej Krevl, http://snap.stanford.edu/data, June 2014.   
% email: jure at cs.stanford.edu                                             
%                                                                            
% wiki-talk temporal network                                                 
%                                                                            
% https://snap.stanford.edu/data/wiki-talk-temporal.html                     
%                                                                            
% Dataset information                                                        
%                                                                            
% This is a temporal network representing Wikipedia users editing each       
% other's Talk page. A directed edge (u, v, t) means that user u edited user 
% v's talk page at time t.                                                   
%                                                                            
% Dataset statistics                                                         
% Nodes   1,140,149                                                          
% Temporal Edges  7,833,140                                                  
% Edges in static graph   3,309,592                                          
% Time span   2320 days                                                      
%                                                                            
% Source (citation)                                                          
% Ashwin Paranjape, Austin R. Benson, and Jure Leskovec. "Motifs in Temporal 
% Networks." In Proceedings of the Tenth ACM International Conference on Web 
% Search and Data Mining, 2017.                                              
%                                                                            
% Jure Leskovec, Daniel P. Huttenlocher, and Jon M. Kleinberg. "Governance in
% social media: A case study of the wikipedia promotion process." ICWSM.     
% 2010.                                                                      
%                                                                            
% Files                                                                      
% File    Description                                                        
% wiki-talk-temporal.txt.gz   talk page edits temporal network               
% wiki-talk-temporal-usernames.txt.gz usernames corresponding to nodes       
%                                                                            
% Data format                                                                
%                                                                            
%     SRC DST UNIXTS                                                         
%                                                                            
% where edges are separated by a new line and                                
%                                                                            
%     SRC: id of the source node (a user)                                    
%     TGT: id of the target node (a user)                                    
%     UNIXTS: Unix timestamp (seconds since the epoch)                       
%                                                                            
% ---------------------------------------------------------------------------
% Notes on inclusion into the SuiteSparse Matrix Collection, July 2018:      
% ---------------------------------------------------------------------------
%                                                                            
% The SNAP graph is 0-based, with nodes numbered 0 to n-1 with n=1,140,149.  
% It is converted to 1-based in the SuiteSparse Matrix Collection.           
%                                                                            
% In the SuiteSparse Matrix Collection, the graph A has 3,309,592 entries.   
% A(i,j) is the number of times user 1+i editted the talk page of user 1+j,  
% at any time (1+ to make the graph 1-based, where i and j refer to node     
% numbers in the SNAP data set).  The usernames are held in                  
% Problem.aux.usernames, as a char array of size 1,140,149-by-229.           
% The kth row of this array (and the kth line of the text file in the        
% MatrixMarket and Rutherford-Boeing format) is the username for the kth row 
% and column of the Problem.A matrix.  The username file in the SNAP data    
% set has both the node number (0 to n-1) and the user name itself; the      
% node number is removed in SuiteSparse collection since it is redundant.    
%                                                                            
% A single user name is blank.  Line 411185 in the SNAP data file            
% wiki-talk-temporal-usernames.txt contains just the string "411184 ".  It   
% is converted here to "user_411185" (1+ to account for the change from      
% 0-based numbering in the SNAP data set to 1-based in the SuiteSparse       
% Matrix Collection).                                                        
%                                                                            
% The temporal edges are held in the Problem.aux.temporal_edges array, of    
% size 7,833,140-by-3, where each row holds a single (source,target,time)    
% edge.  The source and target in this list are 1-based, ranging from 1      
% to n=1,140,149.                                                            
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