- Competing Idea Diffusion Agent Based Model (CID-ABM) 1.0, Elbirt, B.
- This software allows a researcher to investigate the propagation of competing [information] ideas through a [social] network with controls for who starts with the idea [seeds], leadership, adoption time (Solomon, 2000), and dynamic idea adoption [floating decisions]. JUNG (Java Universal Network/Graph Framework) is used for graphical output during simulation. Data outputs include time stamped calculations, adoptions and saturation percentages.
- Gephi - The Open Graph Viz Platform, Bastian, M.
- Gephi is a new open-source network visualization and analysis platform. Installers and documentation are provided for 32- and 64-bit Windows, Mac and Linux.
Features:
* OpenGL visualization engine - scales to 100K nodes
* Format supported
- UCINET DL
- Pajek NET
- GML
- GDF
- GEXF
- CSV
- GraphML
- GraphViz DOT
- Tulip TPL
* Metrics
- Betweenness, Closeness, Eccentricity,
- Diameter, Average shortest path
- Clustering Coefficient
- PageRank
- HITS
* Database import with SQL
* Real-time layout
- FR
- Yifan's Hu MultiLevel
- ForceAtlas
* Community-detection - Modularity (Louvain)
* Filtering - Dynamic queries
* Export Network as SVG, PDF, PNG
* Dynamic Network Analysis (DNA) features - use Timeline component
* Group, expand, collapse clusters from attributes
- Jacob's Ladder 12.1 (2009), Elbirt, B.
- Multidimensional Data Animation, Visualization and Intonation Application for Creating Virtual Reality Displays
Version 12.1 is the last full version released. Unilke previous versions, JL 12 (c) uses OpenGL and Java technologies to display XML network content as defined in NetXML 2.0. The software is provided with full documentation and examples for viewing. Many changes and additions have been done to enhance the outputs including surfaces, spherical axis, edge labels with strengths, spatial spread controls, Alpha size for cylinder, torus and pyramid, animation disable/enable controls, forced edge colors and much more.
- Matrix to Coordinates 2.0 (2009), Elbirt, B.
- This application will take any N x N matrix and create a coordinate system (Reimmann space) based on similarities of the objects. The resulting coordinates work such that the closer two objects are the more similar they are.
Although the program will handle any size data your system memory will allow; the calculation time will vary based on the depth of dimensionality chosen.
This version, unlike M2C 1.0(C), uses the Brandes & Pich (2007) MDS algorithms and a rotation algorithm to perform time series comparisons is built in for use.
The download is available (Java application) with the usage information built in as a help menu and a documentation file is also provided with examples.
- NetDraw software for visualization and analysis of social networks -- FREE, Borgatti, S.
- NetDraw is a free program written by Steve Borgatti for visualizing both 1-mode and 2-mode social network data. It can handle multiple relations at the same time, and can use node attributes to set colors, shapes, and sizes of nodes. Pictures can be saved in metafile, jpg, gif and bitmap formats. The program reads UCINET system files, UCINET DL files, Pajek files, and its own VNA format (which allows saving network and attribute data together, along with layout information like spatial coordinates, colors, etc.). IMPORTANT: If you format data as a VNA file, NETDRAW can handle *very* large files. For example, sparse networks of 3500 nodes are very practical on a machine with 1GB of RAM (more is better). 10,000 nodes works fine with 2GB of RAM (assuming it is very sparse, of course).
- NetMiner - premium software for modeling, analysis and visualization of networks, Ghim, G.
- NetMiner is all-in-one software tool for exploratory analysis and visualization of network data.
Main features include :
- comprehensive network measures and models (both social and general)
- can handle large network data
- both descriptive and statistical network analysis
- plenty of graph-layout algorithms and visual decoration facilities
- built-in multivariate statistical procedures and charts
- visual interactive analysis and what-if simulations
- expressive and flexible network data model
- facilities for management of data and workflow
- user-friendly and professional-looking user interface
- full documentation (1,000+ pages of User's Manual)
For more information and free trial version, visit our website:
http://www.netminer.com
- NetTunes 1.0 (2009), Elbirt, B.
- Listen to your data to find errors, patterns and more! MIDI for the scientific study of data. Current versin includes output to MIDI files (although some systems seem to have problems with them).
Plans for Next Version: Included Example, additional graphs, Information Display Window.
- Network Genie, Hansen, W.
- Network Genie is an online application for designing and managing social network projects. Network Genie is a fee-for-service application, but priced reasonably to encourage broad use.
Network Genie helps you:
• Design network surveys and survey questions. The application handles ego-centric networks, complete networks, and hybrid networks (egos can be giving the option to add names of alters that accumulate within the network). Users can design surveys to meet their needs including both social network and person-centered questions. Social network question formats allow egos to identify subgroups of alters, to rate and rank alters, to identify single alters who most exemplify a quality, and to rate alter-to-alter relationships.
• Manage social network projects. The application allows you to manage network lists and share responsibilities with a team of colleagues.
• Collect social network data using online forms. This includes sending email invitations to participate and monitoring survey completion.
• Download and export data to the social network analysis program of your choice. Formats currently supported include CVS (comma separated variable), Inflow, NEGOPY, Multinet, Pajek, Siena, and UCINet. More formats will become available upon request.
- NetXML 2.1 (2009), Elbirt, B.
- This application (2.1) will convert matrix data into XML files for use with Jacob's Ladder 12.1 (c). Inputs include matrixes, attribute data, link pair data, MS Excel 97 files and more. Coordinate (MDS) generation and rotation are included in this version as well.
Version 2.1 : Rotation was removed due to algorithmic errors and the Load Matrix function is fixed.
- Pajek - analysis and visualization of large networks, Mrvar, A.
- Pajek (Slovene word for Spider) is a program, for Windows, for analysis and visualization of large networks.
It is freely available, for noncommercial use.
Pajek is developed by Vladimir Batagelj and Andrej Mrvar.
A detailed introduction to Pajek is given in the book W. de Nooy, A. Mrvar, V. Batagelj: Exploratory Social Network Analysis with Pajek,
Cambridge University Press, 2005.
- Palantir Government, Swan, D.
- Palantir Government is a platform for information analysis. Palantir was designed for environments where the fragments of data that an analyst combines to tell the larger story are spread across a vast set of starting material. Palantir provides flexible tools to import and model data, intuitive constructs to search against this data, and powerful techniques to iteratively define and test hypotheses. With Palantir, an analyst can go all the way from an initial tasking to a final product in hours or days, rather than weeks.
Platform Overview
- Seamlessly integrates structured and unstructured data sources
- Provides advanced search & discovery capabilities
- Enables enterprise-wide knowledge management
- Facilitates collaboration across users, groups, and agencies
- PermNet, Tsuji, R.
- A permutation test software. It does symmetry and transitivity tests for valued data, and triad census for binary data.
It handles missing values pretty well.
Fortunately, it is cited in Carrington, Scott, and Wasserman's Models and Methods in Social Network Analysis (2005).
- pnet - program for statistical network modeling, Robins, G.
- statistical analysis of social network data - especially using exponential random graph models.
Simulation:
Simulate Exponential Random Graph distributions with given parameters.
Estimation:
Approximate specified network effects or parameters for a given network.
Goodness of Fit:
Test parameter estimates of a model against important features of the observed network.
- R Packages for Network Analysis, Butts, C.
- This page contains information on various scripts and packages for the analysis of network (and other data) withi the R statistical computing system. This includes core packages such as sna and network, as well as more specialized libraries such as nettheory. See also the statnet project web site (http://statnetproject.org).
- Siena - statistical software for network dynamics, Snijders, T.
- SIENA is a program for the statistical analysis of longitudinal social networks, including dynamics of networks and behavior. It is implemented as a package in the statistical system R; the package is called RSiena.
The main approach used by SIENA for modeling dynamics of network (or of networks and behavior) is an actor-oriented model, in which it is assumed that the social actors who are represented by the nodes in the network play a crucial role in changing their ties to other actors; in the case of associated behavior dynamics, also in changing their behavior. All of these models are Markov chain models; such models are more applicable to relations and behavioral variables that can be regarded as states than to relations or behavior that are more adequately regarded as non-enduring events.
The program, being an R package, is open source. The website contains extensive documentation and examples.
- Social Networks Visualiser (SocNetV), Kalamaras, D.
- SocNetV is a cross-platform, user-friendly, graphical application for Social Networks Analysis and Visualisation.
It helps you construct social networks with simple clicks on a virtual canvas or load network files in GraphML format (as well as adjacency, dot, .paj, .dl, etc) and modify them.
The application can compute simple network properties, such as density, diameter and distances, as well as more structural statistics, such as node and network centralities (i.e. closeness, betweeness, graph), clustering coefficient, etc.
SocNetV also supports various layout algorithms (i.e. Spring-embedder, circular and in levels according to various centrality indexes) for meaningful visualisations.
Furthermore, it can create random networks (Erdos-Renyi, Watts-Strogatz, ring lattice, etc) or, more interestingly, crawl a given website and instantly create the network of all links found in the initial page and so on.
Other useful features of SocNetV are the recreation of known data sets (such as Florentine Families, etc) and the triad census.
SocNetV is being developed in Qt, a C++ framework by Nokia, and it is free software, licensed under the GNU Public License version 3 (GPL3).
Download binary packages for Linux and Windows from the project's page:
http://socnetv.sourceforge.net
- Sonamine Graph Scoring Engine (Click here to download free copy), Lim, N.
- The Sonamine Graph Scoring Engine (SGSE) is a high performance engine that runs on a data miner's laptop without any memory limitations. In one simple command, the SGSE loads up a set of arcs/edges and executes the scoring algorithms you want. It can easily score up to 2 million nodes with only 2 GB of memory. It allows you to quickly generate network scores that can then be used in predictive modeling and machine learning tasks. From there, you can determine which models work and what social network metrics you need in production.
Key differences from other software
* Scalable to millions of nodes - not bound by amount of RAM.
* High performance - proprietary software enables efficient representation and high speed processing
* Calculates neighborhood scores not found in common social network analysis tools. Examples include percentage of neighbors with degree 2, size of local network up to 3 hops away, percentage of connected neighbors who meet certain criteria, eg age >40.
* Persistent graph - load graph only once. You can shut down computer and reference same graph for other types of network scoring.
Performance benchmark
* For 1 million edges and 400,000 nodes, on a Windows single core laptop with 2GB physical RAM, loads in under 3 minutes, scores eigenvector centrality in under 3 minutes.
Come to our website to get a free eval copy. Click on the title.
- Statnet Project, Butts, C.
- statnet is a suite of software packages for network analysis that implement recent advances in the statistical modeling of networks. The analytic framework is based on Exponential family Random Graph Models (ergm). statnet provides a comprehensive framework for ergm-based network modeling, including tools for model estimation, model evaluation, model-based network simulation, and network visualization. This broad functionality is powered by a central Markov chain Monte Carlo (MCMC) algorithm.
statnet has a different purpose than the excellent packages UCINET or Pajek; the focus is on statistical modeling of network data. The statistical modeling capabilities of statnet include ERGMs, latent space and latent cluster models. The packages are written in a combination of (the open-source statistical language) R and (ANSI standard) C, and are called from the R command line. And because it runs in the R package (www.r-project.org), you also have access to the full functionality of R, including the packages "network" and "sna." statnet has a command line interface, not a GUI, with a syntax that resembles R.
- statnet: software tools for the representation, visualization, analysis and simulation of social network data., Handcock, M.
- statnet is a suite of software packages for network analysis that implement recent advances in the statistical modeling of networks. The analytic framework is based on Exponential family Random Graph Models (ergm). statnet provides a comprehensive framework for ergm-based network modeling, including tools for model estimation, model evaluation, model-based network simulation, and network visualization. This broad functionality is powered by a central Markov chain Monte Carlo (MCMC) algorithm.
statnet has a different purpose than the excellent packages UCINET or Pajek; the focus is on statistical modeling of network data. The statistical modeling capabilities of statnet include ERGMs, latent space and latent cluster models. The packages are written in a combination of (the open-source statistical language) R and (ANSI standard) C, and are called from the R command line. And because it runs in the R package (www.r-project.org), you also have access to the full functionality of R, including the packages \"network\" and \"sna\" written by Carter Butts. statnet has a command line interface, not a GUI, with a syntax that resembles R.
- tnet: Analysis of weighted networks, two-mode networks, and longitudinal networks, Opsahl, T.
- tnet is a package written in R to serve three purposes:
1. Calculate social network measures on weighted networks
Not everyone is the same. Some people are close to us, whereas others are just acquaintances. Few network measures, and fewer network analysis programmes, can deal with datasets where the ties are differentiated by weights. By removing the weights of relations, we are removing a lot of the richness within the dataset. This means that we are limiting the weight analysis to sensitivity analyses, which are difficult to interpret. A close friendship is not the same as an acquaintance.
2. Calculate social network measures on two-mode networks (also known as affiliation or bipartite networks)
Most forms of interaction occur through mediums, such as meetings, projects, forums, etc. By simply joining two people if they have interacted with the same medium, we greatly reduce the information available to analyse. For example, the clustering coefficient on a one-mode projection of a two-mode network is meaningless as triangles are formed automatically when three or more people interact with the same medium. To remove some of the biases that might invalidate the analysis, a new set of measures directed at analysing two-mode networks directly (and a software were these measures are implemented) are needed.
3. Detect underlying principles that guide tie formation in networks with time-stamped ties (from version 3)
Network analysis is often based on static networks. In these networks there are issues of dependence as everything depends on everything. Therefore it is difficult to say why certain ties are created and others are not. In networks where the exact sequence of ties is know, the endogeneity issue can be dealt with. This type of data is generally from online communities, email networks, and telephone networks (if your dataset is not like this, but collected in waves, try Siena).
tnet is available on CRAN. Please send feedback about the package if you have any issues or suggestions.
- TouchGraph Amazon Browser, Swan, D.
- Free visualization will let you explore the connections between books, music, or movies.
-TouchGraph's Amazon Browser reveals the intricate network structure within purchase pattern recommendations.
-Explore related books or albums, see how similar items form clusters around common subjects, and discover how the clusters themselves are connected within the information space.
Getting Started
1. Make sure you have the latest version of java, at least Java 1.5
2. Choose to search Books, Music, or Movies
3. Enter your search and press \"Graph It!\"
4. Say \"Run\" when asked \"Do you want to trust the signed applet?\"
5. Disable popup blockers to view info on books and albums.
- TouchGraph Facebook Browser, Swan, D.
- Explore your friends' Facebook photos!
-Click 'Launch Browser' to sign in to Facebook and display the visualization.
-The TouchGraph Facebook Browser lets you see how your friends are connected, and who has the most photos together.
-Explore your networks by graphing photos from anyone's album, or view the connections between members of a group.
Getting Started
1. Make sure you have the latest version of java, at least Java 1.5
2. Click \"Launch Browser!\" to start the application.
3. Login to your Facebook account to allow TouchGraph to display your friends and groups.
4. Disable popup blockers to activate links back to profile pages.
\"Facebook\" is a registered trademark of Facebook, Inc. All rights reserved.
- TouchGraph Google Browser, Swan, D.
- Free Java application to explore the connections between related websites.
Getting Started
1. Make sure you have the latest version of java, at least Java 1.5
2. Type in your search keywords or a URL, and press \"Graph It!\"
3. Say \"Run\" when asked \"Do you want to trust the signed applet?\"
4. Disable popup blockers to allow launching websites.
- TouchGraph Navigator, Swan, D.
- Commercial Social Network Analysis Graphing Tool
-100% java technology.
-A range of different relationship types are supported. Edges can be directed, undirected, and can show flow in both directions.
-Text and numerical attributes can be associated with nodes and edges. Tables display the attributes and allow sorting.
-Images can be associated with nodes.
-Advanced cluster computation reveals inherent groupings.
-Co-citations and co-occurrence analysis clarifies dense networks.
-Supports .XLS and other \"standard\" data file layouts
Navigator Help URL: http://www.touchgraph.com/navigatorhelp/
- UCINET Software for Social Network Analysis, Borgatti, S.
- 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.
- UrlNet Python Library, Hunscher, D.
- Mining the Web for Social Networking Data
When studying aspects of the World Wide Web using network analysis tools and techniques, building networks for analysis can be tedious, time-consuming, and error-prone. The UrlNet library, written in the Python scripting language, is intended to provide a powerful, flexible, easy to use, \"spider\"-like mechanism for generating such networks.
UrlNet was originally written with to aid in the analysis of search engine result set quality. This relied on the time-tested method of harvesting links from static or dynamically generated Web pages. Many of its features stem from the demands of this research domain, but have much wider applicability.
** A Tool for the Semantic Web
UrlNet's usefulness is not limited to spidering and link harvesting. Because many data sources focused on a plethora of subjects are also available via Web Services over the Internet, UrlNet can be employed to build networks for many different topic domains. For example, it has been used to look at blogger conversations and biomedical researcher co-citation networks.
- visone - visual analysis of social networks, Brandes, U.
- visone (ital. for mink) is free software written in Java and running on Linux, MacOS, and Windows machines.
It features various standard and non-standard methods for analysis and visualization of networks, and a powerful graphical user interface. It's native file format is GraphML, allowing for arbitrarily many attributes of nodes, links, and networks, but other formats such as CSV tables, UCINet DL, Pajek .net, etc. can be imported. Visualizations can be exported as pdf, png, tiff, svg, or Windows metafiles.
- VisuaLyzer for SNA and visualization, Tien, A.
- VisuaLyzer combines numerous visualization and analysis functions. It has been praised by users regarding its (e.g., : http://netmap.ifpriblog.org/2008/05/25/visualizing-networks-online-for-km4dev) functionality and usability.
VisuaLyzer allows flexible and unlimited definition and specification of types of nodes, node attributes, types of links, and link attributes. It can display overlays of different node and edge attributes using various combinations of colors, shapes, and sizes, and can support various query mechanisms for the displayed network. For example, it supports queries based on the properties of dyads (pairs of nodes) in a network. It allows for nodes to be grouped and ungrouped for display. It provides X-Y plotting of networks based on any selected node attributes. Detailed descriptions of VisuaLyzer functionality are in the User Manual.
The VisuaLyzer installation package can be downloaded from: http://www.MDLogix.com/downloads/VisuaLyzer2.0setup.exe (Note: if installing in Windows Vista, the default installation directory needs to be changed to something like c:\MDLogix.)
VisuaLyzer has been widely used, with tens of thousands of copies downloaded. It continues to be downloaded and adopted by diverse clients, including SNA researchers, public health researchers, program managers, systems engineers, high school math teachers, marketing organizations, military analysts, newspaper reporters(to better understand their sources), and many others. It has been of particular interest to Non-Governmental Organizations (NGOs) working to improve aspects of public health in developing countries.
- VisuaLyzer, EgoNet, LinkAlyzer, Tien, A.
- LinkAlyzer is a highly specialized program that supports users in defining and running matching algorithms to link smaller networks into larger networks, for example to combine egocentric networks into a regional sociometric network. It provides built-in support for managing sets of matching algorithms and datasets. It has been used with datasets with 100s of millions of potential matches.
VisuaLyzer combines numerous visualization and analysis functions. It has been praised by users regarding its (e.g., : http://netmap.ifpriblog.org/2008/05/25/visualizing-networks-online-for-km4dev) functionality and usability.
VisuaLyzer allows flexible and unlimited definition and specification of types of nodes, node attributes, types of links, and link attributes. It can display overlays of different node and edge attributes using various combinations of colors, shapes, and sizes, and can support various query mechanisms for the displayed network. For example, it supports queries based on the properties of dyads (pairs of nodes) in a network. It allows for nodes to be grouped and ungrouped for display. It provides X-Y plotting of networks based on any selected node attributes. Detailed descriptions of VisuaLyzer functionality are in the User Manual.
The VisuaLyzer installation package can be downloaded from: http://www.MDLogix.com/downloads/VisuaLyzer2.0setup.exe (Note: if installing in Windows Vista, the default installation directory needs to be changed to something like c:\MDLogix.)
VisuaLyzer has been widely used, with tens of thousands of copies downloaded. It continues to be downloaded and adopted by diverse clients, including SNA researchers, public health researchers, program managers, systems engineers, high school math teachers, marketing organizations, military analysts, newspaper reporters(to better understand their sources), and many others. It has been of particular interest to Non-Governmental Organizations (NGOs) working to improve aspects of public health in developing countries.
EgoNET: EgoNET is a flexible tool that supports data collection for egocentric or personal networks by allowing researchers to author interviewing instruments, which can then be performed on a Windows computer. EgoNET is actually two Windows applications: EgoNET-QBuilder (for authoring of name generator interviews) and EgoNET-Client (for conducting interviews and collecting data). Each of these has functions that meet many prioritized researcher needs.
The EgoNET installation package can be downloaded from: http://www.MDLogix.com/downloads/EgoNet1.0setup.exe (Note: if installing in Windows Vista, the default installation directory needs to be changed to something like c:\MDLogix.)
Last Updated Thu Jul 29 20:30:02 2010
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