Social network analysis software
Social network analysis software (SNA software) is software which facilitates quantitative or qualitative analysis of social networks, by describing features of a network either through numerical or visual representation.
Networks can consist of anything from families, project teams, classrooms, sports teams, legislatures, nation-states, disease vectors, membership on networking websites like Twitter or Facebook, or even the Internet. Networks can consist of direct linkages between nodes or indirect linkages based upon shared attributes, shared attendance at events, or common affiliations. Network features can be at the level of individual nodes, dyads, triads, ties and/or edges, or the entire network. For example, node-level features can include network phenomena such as betweenness and centrality, or individual attributes such as age, sex, or income. SNA software generates these features from raw network data formatted in an edgelist, adjacency list, or adjacency matrix (also called sociomatrix), often combined with (individual/node-level) attribute data. Though the majority of network analysis software uses a plain text ASCII data format, some software packages contain the capability to utilize relational databases to import and/or store network features.
Visual representations of social networks are important to understand network data and convey the result of the analysis. Visualization often also facilitates qualitative interpretation of network data. With respect to visualization, network analysis tools are used to change the layout, colors, size and other properties of the network representation.
Some SNA software can perform predictive analysis. This includes using network phenomena such as a tie to predict individual level outcomes (often called peer influence or contagion modeling), using individual-level phenomena to predict network outcomes such as the formation of a tie/edge (often called homophily models) or particular type of triad, or using network phenomena to predict other network phenomena, such as using a triad formation at time 0 to predict tie formation at time 1.
Types of Software
Network analysis software generally consists of either packages based on graphical user interfaces (GUIs), or packages built for scripting/programming languages.
In general, the GUI packages are easier to learn, while scripting tools are more powerful and extensible. Widely used, often open-sourced and well-documented GUI packages include EgoWeb 2.0 (open source), NetMiner, UCINet, Pajek (freeware), GUESS, ORA, Cytoscape, Gephi, SocNetV (free software) and muxViz (open source).
Commonly used and well-documented scripting tools used for network analysis include: NetMiner with Python scripting engine, the statnet suite of packages for the R statistical programming language, igraph, which has packages for R and Python, muxViz (based on R statistical programming language and GNU Octave) for the analysis and the visualization of multilayer networks, the NetworkX library for Python, and the SNAP package for large-scale network analysis in C++ and Python. Though difficult to learn, some of these open source packages are growing much faster in terms of functionality and features than privately maintained software, and extensive documentation and tutorials are available.
All of the tools above contain visualization capabilities.
Click the "show" link (next to "Notes") to expand the list.
The suite of innovative solutions can be custom-fit to address specific, persistent issues facing the organization. OA provides leaders with deep understanding of relationships and informal networks within their teams to enable enhanced performance, innovation, and productivity.
|Product||Main Functionality||Input Format||Output Format||Platform||License and cost||Notes|
|AllegroGraph||Graph Database. RDF with Gruff visualization tool||RDF||RDF||Linux, Mac, Windows||Free and Commercial||AllegroGraph is a graph database. It is disk-based, fully transactional OLTP database that stores data structured in graphs rather than in tables. AllegroGraph includes a Social Networking Analytics library.|
|Gephi||Graph exploration and manipulation software||GraphViz(.dot), Graphlet(.gml), GUESS(.gdf), LEDA(.gml), NetworkX(.graphml, .net), NodeXL(.graphml, .net), Pajek(.net, .gml), Sonivis(.graphml), Tulip(.tlp, .dot), UCINET(.dl), yEd(.gml), Gephi (.gexf), Edge list(.csv), databases||GUESS(.gdf), Gephi(.gexf), .svg, .png||Any system supporting Java 1.6 and OpenGL||Open Source (GPL3), seeking contributors||Gephi is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs. It is a tool for people that have to explore and understand graphs. The user interacts with the representation, manipulate the structures, shapes and colors to reveal hidden properties. It uses a 3D render engine to display large networks in real-time and to speed up the exploration. A flexible and multi-task architecture brings new possibilities to work with complex data sets and produce valuable visual results.|
|GraphStream||Dynamic Graph Library||GraphStream(.dgs), GraphViz(.dot), Graphlet(.gml), edge list||GraphStream(.dgs), GraphViz(.dot), Graphlet(.gml), image sequence||Any system supporting Java||Open Source||With GraphStream you deal with graphs. Static and Dynamic.
You create them from scratch, from a file or any source. You display and render them.
|Graph-tool||Python module for efficient analysis and visualization of graphs.||GraphViz(.dot), GraphML||GraphViz(.dot), GraphML and multiple image formats.||GNU/Linux, Mac||Free Software (GPL3)||Graph-tool is a python module for efficient analysis of graphs. Its core data structures and algorithms are implemented in C++, with heavy use of Template metaprogramming, based on the Boost Graph Library. It contains a comprehensive list of algorithms.|
|Graphviz||Graph vizualisation software||GraphViz(.dot)||Multiple image formats.||Linux, Mac, Windows||Open Source (CPL)||Graphviz is open source graph visualization framework. It has several main graph layout programs suitable for social network visualization.|
|InfiniteGraph||Highly scalable, distributed Graph Database.||SNAP, Gremlin, formatted text files for high speed, parallel loading||Gremlin, plus user definable||Linux, Mac, Windows||Commercial||InfiniteGraph is a distributed graph database that can exploit mixed disk, SSD and in-memory algorithms. It is built on a specialized distributed database engine that is optimized for storing objects with large numbers of connections. It supports parallel queries, path definition and link hunting. There is a sample Social Networking Analytics application.|
|Java Universal Network/Graph (JUNG) Framework||network and graph manipulation, analysis, and visualization||built-in support for GraphML, Pajek, and some text formats; user can create parsers for any desired format||built-in support for GraphML, Pajek, and some text formats; user can create exporters for any desired format||Any platform supporting Java||Open source (BSD license)||JUNG is a Java API and library that provides a common and extensible language for the modeling, analysis, and visualization of relational data. It supports a variety of graph types (including hypergraphs), supports graph elements of any type and with any properties, enables customizable visualizations, and includes algorithms from graph theory, data mining, and social network analysis (e.g., clustering, decomposition, optimization, random graph generation, statistical analysis, distances, flows, and centrality (PageRank, HITS, etc.)). It is limited only by the amount of memory allocated to Java.|
|Mathematica||Graph analysis, statistics, data visualization, optimization, image recognition.||CSV, DOT, GraphML, JSON, Pajek, XLS and multiple other non-network formats.||CSV, DOT, GraphML, JSON, Pajek, XLS and multiple other non-network formats.||Windows, Macintosh, Linux||Commercial||Mathematica is a general purpose computation and analysis environment.|
|Network Overview Discovery Exploration for Excel (NodeXL)||Network overview, discovery and exploration||email, .csv (text), .txt, .xls (Excel), .xslt (Excel 2007, 2010, 2013), .net (Pajek), .dl (UCINet), GraphML||.csv (text), .txt, .xls (Excel), .xslt (Excel 2007), .dl (UCINet), GraphML||Windows XP/Vista/7||Free (Ms-PL)||NodeXL is a free and open Excel 2007, 2010, 2013 Add-in and C#/.Net library for network analysis and visualization. It integrates into Excel 2007, 2010, 2013 and adds directed graph as a chart type to the spreadsheet and calculates a core set of network metrics and scores. Supports extracting email, Twitter, YouTube, Facebook, WWW, Wiki and flickr social networks. Accepts edge lists and matrix representations of graphs. Allows for easy and automated manipulation and filtering of underlying data in spreadsheet format. Multiple network visualization layouts. Reads and writes Pajek, UCINet and GraphML files.|
|NetMiner 4||All-in-one Software for Network Analysis and Visualization||.xls(Excel),.xlsx (Excel 2007), .csv(text), .dl(UCINET), .net(Pajek), .dat(StOCNET), .gml; NMF(proprietary)||.xls(Excel),.xlsx (Excel 2007), .csv(text), .dl(UCINET), .net(Pajek), .dat(StOCNET), NMF(proprietary)||Microsoft Windows||Free(Coursework)
|NetMiner is a software tool for exploratory analysis and visualization of large network data. NetMiner 4 embed internal Python-based script engine which equipped with the automatic Script Generator for unskilled users. Then the users can operate NetMiner 4 with existing GUI or programmable script language.
|NetworkX||Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.||GML, Graph6/Sparse6, GraphML, GraphViz (.dot), NetworkX (.yaml, adjacency lists, and edge lists), Pajek (.net), LEDA||GML, Gnome Dia, Graph6/Sparse6, GraphML, GraphViz (.dot), NetworkX (.yaml, adjacency lists, and edge lists), Pajek (.net), and assorted image formats (.jpg, .png, .ps, .svg, et al.)||Open source (GPL and similar)||Free||NetworkX (NX) is a toolset for graph creation, manipulation, analysis, and visualization. User interface is through scripting/command-line provided by Python. NX includes a several algorithms, metrics and graph generators. Visualization is provided through pylab and graphviz.
NX is an open-source project, in active development since 2004 with an open bug-tracking site, and user forums. Development is sponsored by Los Alamos National Lab.
|R||Social network analysis within the versatile and popular R environment||R will read in almost any format data file||R has write capability for most data formats||Windows, Linux, Mac||Open source||R contains several packages relevant for social network analysis:
|Tulip||Social Network Analysis tool||Tulip format (.tlp), GraphViz (.dot), GML, txt, adjacency matrix||.tlp, .gml||Windows Vista, XP, 7/ Linux / Mac OS||LGPL||Tulip is an information visualization framework dedicated to the analysis and visualization of relational data. 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.|
|UNISoN (Social Network Analysis Tool)||Download usenet messages and save SNA output files||Reads from free NNTP servers||Creates CSV files and Pajek .net files||Any system supporting Java||Open Source||A java application that can download Usenet messages from free NNTP servers, show the saved messages, then allow filtering of data to save to a Pajek network file or CSV file. It creates networks using the author of each post. If someone replies to a post, there is a unidirectional link created from the author of the post to the author of the message they are replying to. There is also a preview panel that shows the network visually.|
|Wolfram Alpha||Graph analysis, time series analysis, categorical data analysis||Facebook API||Many formats||Web service||Free||Wolfram Alpha is a general computational knowledge engine answering queries on many knowledge domains. Give it the input "Facebook report" and it will answer queries on analysis of your social network data,|
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