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.

Overview

Networks can consist of anything from families,[1] 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.[2] 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.[3] 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.[4] 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.

Features

Visual representations of social networks are important to understand network data and convey the result of the analysis.[5] 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.[6] 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[7]) 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.

Collection of social network analysis tools and libraries
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[8] 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.
Igraph Efficiently create, manipulate, analyze, and plot graphs in C, Python or R. GraphML, LEDA (.gml), and more GraphML, LEDA (.gml), GraphViz (.dot), and multiple image formats Linux, Mac, Windows Open Source (GPL2) igraph is a library collection for creating and manipulating graphs and analyzing networks. It is written in C and also exists as Python and R packages; an interface for Mathematica is also provided.
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)

and Commercial

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.
  • Analysis of large networks(+10,000,000 nodes), comprehensive network measures and models
  • Both exploratory & confirmatory analysis
  • Interactive visual analytics
  • What-if network analysis
  • Built-in statistical procedures and charts
  • Full documentation(1,000+ pages of User's Manual)
  • Expressive network data model
  • Facilities for data & workflow management
  • Python-based Script workbench and user-friendliness
  • Morphological Analyzer for Semantic network analysis
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 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:
  • igraph is a generic network analysis package;
  • sna performs sociometric analysis of networks;
  • network manipulates and displays network objects;
  • PAFit can analyse the evolution of complex networks by estimating preferential attachment and node fitness;
  • tnet performs analysis of weighted networks, two-mode networks, and longitudinal networks;
  • ergm is a set of tools to analyze and simulate networks based on exponential random graph models exponential random graph models;
  • Bergm provides tools for Bayesian analysis for exponential random graph models;
  • hergm implements hierarchical exponential random graph models;
  • RSiena allows the analyses of the evolution of social networks using dynamic actor-oriented models;
  • latentnet has functions for network latent position and cluster models;
  • degreenet provides tools for statistical modeling of network degree distributions;
  • networksis provides tools for simulating bipartite networks with fixed marginals;
  • multiplex offers tools for the analysis of multiple social networks with algebra;
  • netdiffuseR was designed for the analysis of network diffusion of innovations (and diffusion in general);
  • bipartite provides functions to visualise and calculate indices used to describe bipartite graphs. It focuses on webs, i.e., ecological networks.
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,[9][10]

See also

References
  1. Padgett, John F.; Ansell, Christopher K. (1993). "Robust Action and the Rise of the Medici, 1400-1434" (PDF). American Journal of Sociology. University of Chicago Press. 98 (6): 1259–1319. doi:10.1086/230190. ISSN 0002-9602.CS1 maint: ref=harv (link)
  2. Wasserman & Faust, Social Network Analysis Methods and Applications
  3. Robert Hanneman (20 October 1998). "Introduction to Social Network Methods: Table of Contents". Faculty.ucr.edu. Retrieved 24 October 2012.
  4. "Introduction to Social Network Methods: Chapter 1: Social Network Data". Faculty.ucr.edu. Retrieved 24 October 2012.
  5. "JoSS: Journal of Social Structure". Cmu.edu. Retrieved 24 October 2012.
  6. "Only connect: Felix Grant looks at the application of data analysis software to social networks", Scientific Computing World June 2010: pp 9–10.
  7. "Homophily". Analytictech.com. Retrieved 24 October 2012.
  8. Bastian, M., Heymann, S., & Jacomy, M. (2009, May). Gephi: an open source software for exploring and manipulating networks. In ICWSM (pp. 361-362).
  9. Facebook friends mapped by Wolfram Alpha app BBC News
  10. Wolfram Alpha Launches Personal Analytics Reports For Facebook Tech Crunch

Notes
  • Barnes, J. A. "Class and Committees in a Norwegian Island Parish", Human Relations 7:39-58
  • Borgatti, S. (2002). NetDraw Software for Network Visualization. Lexington, KY: Analytic Technologies.
  • Borgatti, S. E. (2002). Ucinet for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies.
  • Berkowitz, S. D. 1982. An Introduction to Structural Analysis: The Network Approach to Social Research. Toronto: Butterworth.
  • Brandes, Ulrik, and Thomas Erlebach (Eds.). 2005. Network Analysis: Methodological Foundations Berlin, Heidelberg: Springer-Verlag.
  • Breiger, Ronald L. 2004. "The Analysis of Social Networks." Pp. 505–526 in Handbook of Data Analysis, edited by Melissa Hardy and Alan Bryman. London: Sage Publications. Excerpts in pdf format
  • Burt, Ronald S. (1992). Structural Holes: The Structure of Competition. Cambridge, MA: Harvard University Press.
  • Carrington, Peter J., John Scott and Stanley Wasserman (Eds.). 2005. Models and Methods in Social Network Analysis. New York: Cambridge University Press.
  • Christakis, Nicholas and James H. Fowler "The Spread of Obesity in a Large Social Network Over 32 Years," New England Journal of Medicine 357 (4): 370-379 (26 July 2007)
  • Doreian, Patrick, Vladimir Batagelj, and Anuska Ferligoj. (2005). Generalized Blockmodeling. Cambridge: Cambridge University Press.
  • Freeman, Linton C. (2004) The Development of Social Network Analysis: A Study in the Sociology of Science. Vancouver: Empirical Press.
  • Hansen, William B. and Reese, Eric L. 2009. Network Genie Users Manual. Greensboro, NC: Tanglewood Research.
  • Hill, R. and Dunbar, R. 2002. "Social Network Size in Humans." Human Nature, Vol. 14, No. 1, pp. 53–72.Google
  • Jackson, Matthew O. (2003). "A Strategic Model of Social and Economic Networks" (PDF). Journal of Economic Theory. 71: 44–74. doi:10.1006/jeth.1996.0108. pdf
  • Huisman, M. and Van Duijn, M. A. J. (2005). Software for Social Network Analysis. In P J. Carrington, J. Scott, & S. Wasserman (Editors), Models and Methods in Social Network Analysis (pp. 270–316). New York: Cambridge University Press.
  • Krebs, Valdis (2002) Uncloaking Terrorist Networks, First Monday, volume 7, number 4 (Application of SNA software to terror nets Web Reference.)
  • Krebs, Valdis (2008) A Brief Introduction to Social Network Analysis (Common metrics in most SNA software Web Reference.)
  • Krebs, Valdis (2008) Various Case Studies & Projects using Social Network Analysis software Web Reference.
  • Lin, Nan, Ronald S. Burt and Karen Cook, eds. (2001). Social Capital: Theory and Research. New York: Aldine de Gruyter.
  • Mullins, Nicholas. 1973. Theories and Theory Groups in Contemporary American Sociology. New York: Harper and Row.
  • Müller-Prothmann, Tobias (2006): Leveraging Knowledge Communication for Innovation. Framework, Methods and Applications of Social Network Analysis in Research and Development, Frankfurt a. M. et al.: Peter Lang, ISBN 0-8204-9889-0.
  • Manski, Charles F. (2000). "Economic Analysis of Social Interactions". Journal of Economic Perspectives. 14 (3): 115–36. doi:10.1257/jep.14.3.115. via JSTOR
  • Moody, James, and Douglas R. White (2003). "Structural Cohesion and Embeddedness: A Hierarchical Concept of Social Groups." American Sociological Review 68(1):103-127.
  • Newman, Mark (2003). "The Structure and Function of Complex Networks" (PDF). SIAM Review. 45 (2): 167–256. arXiv:cond-mat/0303516. Bibcode:2003SIAMR..45..167N. doi:10.1137/S003614450342480. Archived from the original (PDF) on 16 February 2008.
  • Nohria, Nitin and Robert Eccles (1992). Networks in Organizations. second ed. Boston: Harvard Business Press.
  • Nooy, Wouter d., A. Mrvar and Vladimir Batagelj. (2005). Exploratory Social Network Analysis with Pajek. Cambridge: Cambridge University Press.
  • Scott, John. (2000). Social Network Analysis: A Handbook. 2nd Ed. Newberry Park, CA: Sage.
  • Tilly, Charles. (2005). Identities, Boundaries, and Social Ties. Boulder, CO: Paradigm press.
  • Valente, Thomas. (1995). Network Models of the Diffusion of Innovation. Cresskill, NJ: Hampton Press.
  • Wasserman, Stanley, & Faust, Katherine. (1994). Social Networks Analysis: Methods and Applications. Cambridge: Cambridge University Press.
  • Watkins, Susan Cott. (2003). "Social Networks." Pp. 909–910 in Encyclopedia of Population. rev. ed. Edited by Paul Demeny and Geoffrey McNicoll. New York: Macmillan Reference.
  • Watts, Duncan (1999). Small worlds : the dynamics of networks between order and randomness. Princeton, N.J: Princeton University Press. ISBN 978-0-691-11704-1. OCLC 40602717.CS1 maint: ref=harv (link)
  • Watts, Duncan. (2004). Six Degrees: The Science of a Connected Age. W. W. Norton & Company.
  • Wellman, Barry (1999). Networks in the Global Village. Boulder, CO: Westview Press.
  • Wellman, Barry (2001). "Physical Place and Cyberplace: The Rise of Personalized Networking". International Journal of Urban and Regional Research. Wiley. 25 (2): 227–252. doi:10.1111/1468-2427.00309. ISSN 0309-1317.CS1 maint: ref=harv (link)
  • Wellman, Barry and Berkowitz, S.D. (1988). Social Structures: A Network Approach. Cambridge: Cambridge University Press.
  • Weng, M. (2007). "A Multimedia Social-Networking Community for Mobile Devices Interactive Telecommunications Program". Tisch School of the Arts/ New York University. CiteSeerX 10.1.1.538.7640. Cite journal requires |journal= (help)
  • White, Harrison, Scott Boorman and Ronald Breiger. 1976. "Social Structure from Multiple Networks: I Blockmodels of Roles and Positions." American Journal of Sociology 81: 730-80.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.