%-------------------------------------------------------------------------------
% SuiteSparse Matrix Collection, Tim Davis
% https://sparse.tamu.edu/SNAP/sx-mathoverflow
% name: SNAP/sx-mathoverflow
% [SNAP network: Math Overflow temporal network]
% id: 2793
% 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 temporal_edges_a2q temporal_edges_c2a temporal_edges_c2q nodeid A2Q C2A C2Q
% 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                                             
%                                                                            
% Math Overflow temporal network                                             
%                                                                            
% https://snap.stanford.edu/data/sx-mathoverflow.html                        
%                                                                            
% Dataset information                                                        
%                                                                            
% This is a temporal network of interactions on the stack exchange web site  
% Math Overflow (http://mathoverflow.net/). There are three different types  
% of interactions represented by a directed edge (u, v, t):                  
%                                                                            
% user u answered user v's question at time t (in the graph                  
% sx-mathoverflow-a2q) user u commented on user v's question at time t (in   
% the graph sx-mathoverflow-c2q) user u commented on user v's answer at time 
% t (in the graph sx-mathoverflow-c2a)                                       
%                                                                            
% The graph sx-mathoverflow contains the union of these graphs. These graphs 
% were constructed from the Stack Exchange Data Dump. Node ID numbers        
% correspond to the 'OwnerUserId' tag in that data dump.                     
%                                                                            
% Dataset statistics (sx-mathoverflow)                                       
% Nodes   24,818                                                             
% Temporal Edges  506,550                                                    
% Edges in static graph   239,978                                            
% Time span   2350 days                                                      
%                                                                            
% Dataset statistics (sx-mathoverflow-a2q)                                   
% Nodes   21,688                                                             
% Temporal Edges  107,581                                                    
% Edges in static graph   90,489                                             
% Time span   2350 days                                                      
%                                                                            
% Dataset statistics (sx-mathoverflow-c2q)                                   
% Nodes   16,836                                                             
% Temporal Edges  203,639                                                    
% Edges in static graph   101,329                                            
% Time span   2349 days                                                      
%                                                                            
% Dataset statistics (sx-mathoverflow-c2a)                                   
% Nodes   13,840                                                             
% Temporal Edges  195,330                                                    
% Edges in static graph   81,121                                             
% Time span   2350 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.                                              
%                                                                            
% Files                                                                      
% File    Description                                                        
% sx-mathoverflow.txt.gz  All interactions                                   
% sx-mathoverflow-a2q.txt.gz  Answers to questions                           
% sx-mathoverflow-c2q.txt.gz  Comments to questions                          
% sx-mathoverflow-c2a.txt.gz  Comments to answers                            
%                                                                            
% 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 1-based, with nodes in all graphs numbered 1 to          
% n=88,580.                                                                  
%                                                                            
% In the SuiteSparse Matrix Collection, the primary matrix, Problem.A, is    
% the overall static graph, with 239,978 edges, of size n-by-n with          
% n=24,818.  These edges represent the 506,550 temporal edges.  A(i,j) is    
% the number of times person u=nodeid(i) interacted with person v=nodeid(j), 
% with a temporal edge (u,v,t), with any kind of interaction.                
% Problem.aux.nodeid is a list of the node id's that appear in the SNAP data 
% set.                                                                       
%                                                                            
% A2Q = Problem.aux.Q2A is the static sx-mathoverflow-a2q graph.             
% C2Q = Problem.aux.C2Q is the static sx-mathoverflow-c2q graph.             
% C2A = Problem.aux.C2A is the static sx-mathoverflow-c2a graph.             
% These sum together to give the the overall graph.  That is,                
% A = A2Q + C2Q + C2A.                                                       
%                                                                            
% A2Q(u,v) is the number of times person u answered v's questions.           
% C2Q(u,v) is the number of times person u commented on v's question.        
% C2A(u,v) is the number of times person u commented on v's answer.          
%                                                                            
% The temporal edges are held in:                                            
% Problem.aux.temporal_edges:     [506550x3]                                 
% Problem.aux.temporal_edges_a2q: [107581x3]                                 
% Problem.aux.temporal_edges_c2q: [203639x3]                                 
% Problem.aux.temporal_edges_c2a: [195330x3]                                 
%                                                                            
% Each row in these matrices is a single temporal edge, (u,v,t).  Summing up 
% all entries in A gives 506,550, and likewise the sum of entries in the     
% other graphs gives the number of temporal edges they represent.            
%-------------------------------------------------------------------------------
