Pointers to various network resources follow, including network datasets, analysis and visualization software; as well as other Network Science courses offering valuable material and readings. These could be helpful for your project, and hopefully for your research on networks down the road. I will be continuously updating the lists, so please let me know if you come across something worth adding.


Network datasets

Prominent researchers and institutions have been compiling valuable network datasets for use of the research community.

  • compiled by . You can also take a look at their collection of , and their own list of
  • is a scientific network data repository with interactive visual analytics tools.
  • The with information of more than a billion trips. contains data on over 4.5 million Uber pickups in New York City from April to September 2014, and 14.3 million more Uber pickups from January to June 2015.
  • compiled by the .
  • The hosts datasets from a collection of many different social media sites.
  • A list of network datasets used in 's book on may be found .
  • The offers a social review dataset including a nearly 1 million edge social graph.
  • compiled over the years by .
  • The is an effort to facilitate the scientific study of networks; see also their own list of
  • The offers access to the network topologies studied by .
  • is a project to collect large network datasets of all types in order to perform research in network science and related fields, collected by the at the University of Koblenz-Landau.
  • A compiled by .
  • network cataloge, repository and centrifuge. From the creators of .
  • The research lab at the University of Minnesota host the Movielens dataset, a benchmark for recommendation systems.

Network software

The sheer variety of software available for the study of large-scale graphs mirrors the number of communities involved in such work. While e.g., could be used to implement many of the network analysis algorithms studied in this class, efficiently dealing with large-scale network calls for custom-made graph analytics tools. Some useful network analysis and visualization software packages follow.

  • is a general purpose, high performance system for analysis and manipulation of large networks. is a Python interface for SNAP. To get going with SNAP, you can check the following .
  • is probably the most popular Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Other libraries offering similar functionalities, but likely faster and more scalable implementations are , (also in C and R), and .
  • is popular library for deep learning on graphs and other irregular structures, also known as geometric deep learning.
  • The is a recent package for graph neural networks and machine learning on graphs. It has the advantange of being framework agnostic (build models in PyTorch, TensorFlow or MXNet).
  • is a recent package for signal processing on graphs (e.g., implementing the graph Fourier transform, graph filters, graphs learning, signal interpolation and denoising). Leveraging these graphs signal processing fundamentals and intuitions, the library offers PyTorch implementations. is a Tensorflow variant.
  • is a MATLAB toolbox for complex-network analysis of structural and functional brain-connectivity data sets.
  • is a peta-scale graph mining system, fully written in Java. It runs in parallel, distributed manner on top of
  • is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network.
  • The software package is network motif finding tool; see also their pointers to other related software.
  • is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams.
  • is an open-source interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs.
  • is a freely available Windows-based package for the visualization of large networks.
  • is open-source graph visualization software.
  • is a large networks visualization tool based on the k-core decomposition of a graph.

Network Science courses

See below a few links to several other great Network Science-related classes. Note that depending on the background of the instructor, the focus could vary accordingly.

  • by and (who also offers ).
  • by .
  • by ; check out also his .
  • by .
  • Video webcast of a short course on by .
  • The tensor analysis and graph mining sections of by ; check out some of his on graphs.