Datasets: small ----> large

• Kenneth Massey's Information Retrieval webpage: look under the "Data" section in the middle of the page.
  
  
• Panayiotis Tsaparas' University of Toronto Dissertation webpages1 2
  
  
• C code for turning adjacency list into matrix
  
  
• Matlab m-file for turning adjacency list into matrix
  
  
• Jon Kleinberg's The Structure of Information Networks Course webpage: look under the "Network Datasets" section at the bottom of the page.
  
  
• sample m-file for importing adjacency list into Matlab as PageRank matrix
  
  
• Albert Barabasi's Center for Complex Networks Research webpage: look under the "Resources" section of the menu.
  
  
• sample m-file for importing adjacency list into Matlab as PageRank matrix
  
  
• Sep Kamvar's Stanford webpage: look under the "Data" and "Teaching" sections at the bottom of the page.
  
  
• sample m-file for importing adjacency list into Matlab as PageRank matrix
  
  
• David Gleich's Stanford webpage: the "Publications" and "Programs" sections contain papers and code for the PageRank problem.
  
  
• Mike Thelwall's Statistical Cybermetrics Research Group webpage: look under the "Resources" tab at the top of the page.
  
  

Code

Crawlers: smaller ----> larger-scale implementation

• surfer.m: from Cleve Moler's new book, Numerical Computing with Matlab
  
  
• Webbot: from Ken Massey's work
  
  
• SocSciBot 3: from Mike Thelwall's Statistical Cybermetrics Research Group
  
  
• WebBase: Stanford WebBase Project
  
  
• WebGraph: Graph Compression Tools
  
  

Algorithms

• Various Matlab implementations of vanilla-flavored PageRank power algorithm: by Kamvar, by Moler, by Massey, by Langville
  
  
• Matlab implementation of Personalized PageRank power algorithm: by Langville
  
  
• Matlab implementation of Personalized PageRank power algorithm with Aitken Extrapolation: by Langville
  
  
• Matlab implementation of Personalized PageRank power algorithm with Quadratic Extrapolation: by Langville
  
  
• Matlab suite of m-files containing PageRank power, PageRank Gauss-Seidel, PageRank BiCGSTAB, PageRank GMRES, PageRank Arnoldi, and Personalized PageRank algorithms: by Gleich