NodeXL
| Developer(s) | Social Media Research Foundation |
|---|---|
| Initial release | July 2008[1] |
| Stable release | 1.0.1.238
/ 8 April 2013 |
| Written in | C#, .NET |
| Operating system | Windows |
| Size | 7.8 MB |
| Available in | English |
| Type | Data analysis, Data visualization |
| License | Microsoft Public License |
| Website | nodexlgraphgallery |
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NodeXL is a network analysis and visualization software package for Microsoft Excel 2007/2010/2013/2016.[2][3] The free version contains network visualization and social network analysis features. The commercial version includes access to social media network data importers, advanced network metrics, and automation. It is a popular[n 1] package similar to other network visualization tools such as Pajek, UCINet, and Gephi.[5].
Codebase
NodeXL is a set of prebuilt class libraries using a custom Windows Presentation Foundation control.[6] Additional .NET assemblies can be developed as "plug-ins" to import data from outside data providers. Currently-implemented data providers for NodeXL include Facebook, Twitter, Wikipedia (the MediaWiki understructure), web hyperlinks, Microsoft Exchange Server.[7]
Features
NodeXL is intended for users with little or no programming experience to allow them to collect, analyze, and visualize a variety of networks.[8] NodeXL integrates into Microsoft Excel 2007, 2010, 2013 and 2016 and opens as a workbook with a variety of worksheets containing the elements of a graph structure such as edges and nodes. NodeXL can also import a variety of graph formats such as edgelists, adjacency matrices, GraphML, UCINet .dl, and Pajek .net.
Data Import
NodeXL Pro imports UCINet and GraphML files, as well as Excel spreadsheets containing edge lists or adjacency matrices, into NodeXL workbooks. NodeXL Pro also allows for quick collection of social media data via a set of import tools which can collect network data from e-mail, Twitter, YouTube, and Flickr. NodeXL requests the user's permission before collecting any personal data and focuses on the collection of publicly available data, such as Twitter statuses and follows relationships for users who have made their accounts public. These features allow NodeXL users to instantly get working on relevant social media data and integrate aspects of social media data collection and analysis into one tool.
Data Representation
NodeXL workbooks contain four worksheets: Edges, Vertices, Groups, and Overall Metrics. The relevant data about entities in the graph and relationships between them are located in the appropriate worksheet in row format. For example, the edges worksheet contains a minimum of two columns, and each row has a minimum of two elements corresponding to the two vertices that make up an edge in the graph. Graph metrics and edge and vertex visual properties appear as additional columns in the respective worksheets. This representation allows the user to leverage the Excel spreadsheet to quickly edit existing node properties and to generate new ones, for instance by applying Excel formulas to existing columns.
Graph Analysis
NodeXL Pro contains a library of commonly used graph metrics: centrality, clustering coefficient, diameter. NodeXL differentiates between directed and undirected networks. NodeXL Pro implements a variety of community detection algorithms to allow the user to automatically discover clusters in their social networks.
Graph Visualization
NodeXL generates an interactive canvas for visualizing graphs. The project allows users to pick from several well-known Force-directed graph drawing layout algorithms such as Fruchterman-Reingold and Harel-Koren. NodeXL allows the user to multi-select, drag and drop nodes on the canvas and to manually edit their visual properties (size, color, and opacity). In addition, NodeXL allows users to map the visual properties of nodes and edges to metrics it calculates, and in general to any column in the edges and vertices worksheet.
Research
NodeXL has been used by news outlets like Foreign Policy to visualize the structure of conversations about political topics as well as organizations like the World Bank to analyze voting data.[9][10][11] NodeXL has been used as an analytical tool in dozens[n 2] of research papers in the social, information, and computer sciences as well as the focus of research in human computer interaction, data mining, and data visualization.[13][14][15] [16]
See also
- File formats
- GraphML (NodeXL Pro only)
- Geographic Data Files
- GEFX
- Pajek
- Related software
Notes
References
- ^ Change History, Social Media Research Foundation
- ^ Smith, Marc A.; Shneiderman, Ben; Milic-Frayling, Natasa; Rorigues, Eduarda; Barash, Vladimir; Dunne, Cody; Capone, Tony; Perer, Adam; Gleave, Eric (2009), "Analyzing (social media) networks with NodeXL", Proceedings of the Fourth International Conference on Communities and Technologies, ACM: 255–264, CiteSeerX 10.1.1.147.5521, doi:10.1145/1556460.1556497, ISBN 978-1-60558-713-4
- ^ Hansen, Derek L.; Shneiderman, Ben; Smith, Marc (2010), Analyzing social media networks with NodeXL: Insights from a Connected World, Morgan Kaufmann, ISBN 9780123822291
- ^ NodeXL: Network Overview, Discovery, and Exploration for Excel, Social Media research Foundation, retrieved May 13, 2013
- ^ Marin, Alexandra; Wellman, Barry (2011), "Social network analysis: An Introduction", The Sage Handbook of Social Network Analysis, London, UK: Sage, pp. 11–25, ISBN 9781847873958,
...social network analysts have developed a number of software applications to analyze social network data. The most commonly used are: Pajek, UCINet, MultiNet, Siena, P*/ERGM, R, and NodeXL
- ^ For Programmers: About NodeXL Graph Data Providers, Social Media Research Foundation, retrieved May 13, 2013
- ^ Third-Party Graph Data Importers, Social Media Research Foundation, retrieved May 13, 2013
- ^ Bonsignore, E.M.; Dunne, Cody; Rotman, D.; Smith, M.; Capone, T.; Hansen, D.L.; Shneiderman, B. (2009), "First Steps to Netviz Nirvana: Evaluating Social Network Analysis with NodeXL" (PDF), International Conference on Computational Science and Engineering: 332–339, CiteSeerX 10.1.1.296.6307, doi:10.1109/CSE.2009.120, ISBN 978-1-4244-5334-4
- ^ Allnutt, Luke (April 11, 2012), "Pictures at a Revolution", Foreign Policy, retrieved May 13, 2013
- ^ "Visualizing the War on Women", Foreign Policy, June 18, 2012
- ^ Moeller, Susan (November 18, 2009), You Know and Use Web 2.0 Tools. What About Those of Science 2.0?, The World Bank, retrieved May 13, 2013
- ^ Google Scholar - "nodexl network", retrieved May 13, 2013
- ^ Dunne, Cody; Shneiderman, Ben (2013), "Motif Simplication: Improving Network Visualization Readability with Fan, Connector, and Clique Glyphs" (PDF), Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM: 3247, doi:10.1145/2470654.2466444, ISBN 978-1-4503-1899-0
- ^ Shneiderman, Ben; Dunne, Cody (2012), "Interactive network exploration to derive insights: filtering, clustering, grouping, and simplification" (PDF), Proceedings of the 20th International Conference on Graph Drawing, Lecture Notes in Computer Science, 7704: 2, doi:10.1007/978-3-642-36763-2_2, ISBN 978-3-642-36762-5
- ^ Mendes Rodrigues, Eduarda; Milic-Frayling, Natasa; Smith, Marc; Shneiderman, Ben; Hansen, Derek (2011), "Group-In-a-Box Layout for Multi-faceted Analysis of Communities", Proceedings of the 3rd IEEE International Conference on Social Computing, IEEE: 354, CiteSeerX 10.1.1.296.6410, doi:10.1109/PASSAT/SocialCom.2011.139, ISBN 978-1-4577-1931-8
- ^ Himelboim, Itai; McCreery, Stephen; Smith, Marc (2013-01-01). "Birds of a Feather Tweet Together: Integrating Network and Content Analyses to Examine Cross-Ideology Exposure on Twitter". Journal of Computer-Mediated Communication. 18 (2): 40–60. doi:10.1111/jcc4.12001. ISSN 1083-6101.
- Hansen, DL (2011). "Exploring social media relationships". On the Horizon. 19 (1): 43–51. doi:10.1108/10748121111107726.
- Hansen, DL, Smith, MA, Shneiderman, B (2011) EventGraphs: Charting Collections of Conference Connections. In Forty-Fourth Annual Hawaii International Conference on System Sciences (HICSS). Also see EventGraph SlideShare Presentation
- Hansen, DL, Shneiderman, B, Smith, MA (2010). Visualizing threaded conversation networks: mining message boards and email lists for actionable insights (PDF). Lecture Notes in Computer Science. Vol. 6335. pp. 47–62. doi:10.1007/978-3-642-36763-2_2. ISBN 978-3-642-36762-5.
{{cite book}}:|journal=ignored (help)CS1 maint: multiple names: authors list (link) - Hansen, D, Rotman, D, Bonsignore, E, Milic-Frayling, N, Rodrigues, E, Smith, M, Shneiderman, B . Do You Know the Way to SNA?: A Process Model for Analyzing and Visualizing Social Media Data. HCIL-2009-17 Tech Report.