Network Analysis

1. MatlabBGL is a Matlab package for working with graphs. MatlabBGL is designed to work with large sparse graphs with hundreds of thousands of nodes. It offers a combination of tools for graph-theoretic calculations, network analysis, network graph generation, and visualization.

2. SNAP is a C++ libary for working with massive network datsets (Windows, Linux, Mac).

3. igraph is a package for the generating, manipulating, analyzing, and visualizing network graphs, of sizes up to millions of vertices and edges. (This package is also implemented as a C library and a Python extension module.)

4. statnet is a suite of software packages for network analysis and modeling, that allows for the estimation, evaluation, and simulation of network models, as well as network analysis and visualization. The network models include exponential random graph models (ERGMs) and latent variable models. Model fitting and evaluation is driven by a core of appropriate MCMC algorithms.

5. Brain Connectivity Toolbox provides an access to a large selection of complex network measures in Matlab.

6. Network Workbench is a Large-Scale Network Analysis, Modeling and Visualization Toolkit for Biomedical, Social Science and Physics Research

7. Software for New Benchmark Graphs in Community Detection allows to build networks with community structure where the distributions of nodes’ degree and community size are power-laws with tunable exponents. These networks can be used as benchmark graphs for community detection.

8. Maximum likelihood fits to power-law distributions tools for fitting heavy-tailed distributions to data.

9. StOCNET is a software for analysis of social networks by a variety of stochastic/statistical models.

10. tnet is a package written in R to serve three purposes: 1) Calculate social network measures on weighted networks 2) Calculate social network measures on two-mode networks (also known as affiliation or bipartite networks) 3) Detect underlying principles that guide tie formation in networks with time-stamped ties.

11. Network packages in R. There are a number of other packages in R to perform structural/social network analysis: egonet, epinet, ergm, igraph, inetwork, net models, Siena, sna, statnet, tnet.

12. NetEvo is a computing framework and collection of end-user tools designed to allow researchers to investigate evolutionary aspects of dynamical complex networks.

13. GNS3 is a graphical network simulator that allows simulation of complex networks.

14. Epigrass is a framework for the construction and simulation of complex network epidemiology models.

15. NetworX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
to install it you need to watch this video

16. OslomOSLOM means Order Statistics Local Optimization Method and it’s a clustering algorithm designed for networks.

17. NodeXLNodeXL is the network overview, discovery, and exploration add-in for Excel 2007. It adds social network analysis and visualization features to the familiar spreadsheet, allowing graph metrics to be easily calculated and visualizations of networks to be quickly created.

18. LFR benchmark is a network generators with such realistic properties. Currently, we use LFR-Benchmark generator, which produces networks with power-law degree distribution and with implanted communities within the network.

19. UCINET is a comprehensive package for the analysis of social network data as well as other 1-mode and 2-mode data, Can read and write a multitude of differently formatted text files, as well as Excel files. Can handle a maximum of 32,767 nodes (with some exceptions) although practically speaking many procedures get too slow around 5,000 – 10,000 nodes. Social network analysis methods include centrality measures, subgroup identification, role analysis, elementary graph theory, and permutation-based statistical analysis. In addition, the package has strong matrix analysis routines, such as matrix algebra and multivariate statistics.Integrated with UCINET is the NetDraw program for drawing diagrams of social networks. In addition, the program can export data to Mage and Pajek.

20. Visone is a long-term research project (team), in which models and algorithms to integrate and advance the analysis and visualization of social networks are being developed. An important part of visone is the design and implementation of a software tool intended for research and teaching in social network analysis. It is specifically designed to allow experts and novices alike to apply innovative and advanced visual methods with ease and accuracy.

21. JUNG (Java Universal Network/Graph Framework) 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. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). As an open-source library, JUNG provides a common framework for graph/network analysis and visualization.

22. LibSNA is an open-source library for Social Network Analysis, licensed under the LGPL. This library is under active development by Abe Usher in hopes that it will serve as a catalyst for improving the field of Social Network Analysis. Features:Easy to use Python API -Flexible data import options –Scalable-Built-in reports -Built-in data export capabilities -Open source – easily extended -Fast processing time (efficient use of graph algorithms)

23. Brainwaver. This package computes the correlation matrix for each scale of a wavelet decomposition, namely the one performed by the R package waveslim (Whitcher, 2000). An hypothesis test is applied to each entry of one matrix in order to construct an adjacency matrix of a graph. The graph obtained is finally analysed using the small-world theory (Watts and Strogatz, 1998) and using the computation of efficiency (Latora, 2001), tested using simulated attacks. The brainwaver project is complementary to the camba project for brain-data preprocessing. A collection of scripts (with a makefile) is avalaible to download along with the brainwaver package, see information on the webpage mentioned below.

24. NetworkAnalysis. Network analysis refers to the utilization of graph theory for the analysis of a range of different types of connectivity data. The set of objects contained in this package will be particularly useful for the analysis of groups of networks in neuroimaging, where several populations of subject-specific networks are available. Future versions will include the derivation of SPNs (statistical parametric networks). This revised version of the package now includes C++ codes, which permit to speed up the computational cost of the main cost-integration routines.


Network Visualization

1. Pajek is a freely available (for non-commerical use) Windows-based package for the visualization of large networks. It also has a suite of network analysis tools, mainly oriented towards social network analysis. There is a non-trivial time investment up front necessary to acclimate oneself to the unique input format and the GUI interface. However, the software is capable of producing high-quality network visualizations allowing for a great deal of fine tuning.

2. GUESS is an exploratory data analysis and visualization tool for graphs and networks.

3. Graphviz is an open-source software for graph visualization, developed by researchers at AT&T. Like Pajek, it allows for a variety of high-quality layouts. Graphviz has been used by other packages as the muscle behind their own graph visualization capabilities.

4. Lanet-vi is a tool for the visualization of the k-core structure of large scale graphs

5. SoNIA is a Java-based package for visualizing dynamic or longitudinal “network” data.

6. yEd is a very powerful graph editor that can be used to quickly and effectively generate drawings and to apply automatic layouts to a range of different diagrams and networks.

7. Info Vis Cyberinfrastructure is a software framework for information visualization (Linux, MacOSX, Windows).

8. Analytic Technologies is a software for social network analysis (Windows).

9. NetworkX is a python package for the study of the structure of complex networks.

10. Gephi is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs.

11. Cytoscape is an open source software platform for visualizing complex networks and integrating these with any type of attribute data.

12. Tulip aims to provide the developer with a complete library, supporting the design of interactive information visualization applications for relational data that can be tailored to the problems he or she is addressing.Written in C++ the framework enables the development of algorithms, visual encodings, interaction techniques, data models, and domain-specific visualizations. One of the goal of Tulip is to facilitates the reuse of components and allows the developers to focus on programming their application.

Complex Networks