[CITASA] great resources!

Shelia Cotten cotten at uab.edu
Thu Jun 20 12:21:52 EDT 2013

Dear CITASA colleagues,

I just wanted to pass along the many nodexl resources available I saw earlier today on their website. As someone who wasn’t trained to code, it seems like this simplifies network analysis substantially to me. Great graphs, data, etc. on the site too! And, created by a sociologist and other colleagues.




I hope you will be interested in the following NodeXL [1] project updates from the Social Media Research Foundation [2]!

NodeXL is the free and open add-in for Excel that supports network overview, discovery and exploration.

The code and application can be found at http://www.codeplex.com/nodexl.

Technical questions can be asked on our discussion boards on our Codeplex site [3].  Join us for office hours each Thursday at 10AM Pacific Time in a Google hangout: check Twitter for details prior to each session.

NodeXL has been downloaded more than 190,000 times and is becoming the easiest path to getting insights from network data.  If you can make a pie chart in a spreadsheet, you can now make a network visualization.
We recently added a new data source provider for importing networks stored within Exchange servers and Facebook into NodeXL.

See: http://exchangespigot.codeplex.com/
See: http://socialnetimporter.codeplex.com/

Message board data sets can be analyzed with ThreadMill, the social accounting engine for conversations on the web.  ThreadMill generates networks created when people reply, comment, and communicate.

See: https://github.com/SMRFoundation/ThreadMill

Content analysis features have also been recently integrated.  An example of the analysis of content within sub-groups in the social media networks can be seen in this slide deck:

See: http://www.slideshare.net/Marc_A_Smith/20120622-web-sci12wonmarc-smithsemantic-and-social-network-analysis-of-social-media-with-nodexl

A collection of social media network maps created with NodeXL is on the web [4].

NodeXL Visualizations and data sets can be found here:


[20111210-NodeXL-GraphGallery Home.png]

For background and resources related to our project, please have a look at:

* NodeXLGraphGallery: A collection of social media network visualizations, descriptions, and data sets for download:


* Connected Action Blog about social media, sociology, information visualization, and networks:


* Download and support site for "NodeXL" - the network overview, discovery and exploration add-in for Excel.  If you can make a pie chart, you can now make a social media network map.


* The Social Media Research Foundation creates NodeXL and fosters the creation of open tools, open data, and open scholarship:


* Recent press: Applying social media network maps to political topics:




* Video: overview of NodeXL






* Slides: overview of the NodeXL project and its applications




NodeXL supports the exploration of social media with import features that pull data from personal email indexes on the desktop, Twitter, Flickr, Youtube, Facebook and WWW hyper-links.

NodeXL allows non-programmers to quickly generate useful network statistics and metrics and create visualizations of network graphs.  Filtering and display attributes can be used to highlight important structures in the network.  Innovative automated layouts make creating quality network visualizations simple and quick:
General NodeXL news can often be found on the Connected Action blog [5] and a recent video and slide deck describing the application of NodeXL to generate social media maps is also available [6].

A video tutorial for NodeXL [7]  a manuscript tutorial guide to NodeXL created at the University of Maryland, College of Information Studies [8] along with supporting data sets [9]

A book Analyzing Social Media Networks with NodeXL: Insights from a connected world is available from Morgan-Kaufmann [10].

Recent slide decks describe NodeXL [11] [12] along with a video from the PDF2010 conference [13].

NodeXL allows for the import of network data in the form of edge lists, matrices, graphML, UCINet, and Pajek files along with CSV and other workbooks.

Recent features added to NodeXL include faster metrics calculation, automated graph processing, larger data sets, new layouts, scales, axes, and legends. NodeXL can perform scheduled data collection for standing queries from a desktop server that can be triggered from Windows Scheduler.  Scheduled data collections can start automated data processing of collected networks.  NodeXL lets users set their configurations once and apply those sets of steps to hundreds of other graphs with a few clicks.

Recent NodeXL Topics and Features:

   > Graph Process Automation
   > Collect nodes into groups
   > Group metrics
   > Groups collapse/expand
   > Group by cluster, connected components, and manual
   > Group layout creates innovative visualizations
   > Scheduled collection/desktop server
   > Map data to display attributes easily with "Autofill columns"
   > Better edge label control, conditional labels
   > Shapes and images
   > Background images: Fake geo-maps
   > Filter by dates
   > Bug fixes: Twitter, setup, multiple users, settings, locked down machines

In partnership with the Uberlink corporation [14], the VOSON data collector component has recently been integrated into NodeXL to enable web hyperlink network extraction.

NodeXL requires Office 2007.  Other versions of Excel (like 2008 on Mac, or the older 2003) do not work with NodeXL (sorry!).  NodeXL works with the new Office 2010 version of Excel.

NodeXL is a project from the Social Media Research Foundation and receives generous support from its users!  Contributors to NodeXL include the Microsoft Research External Projects Group [15], Natasa Milic-Frayling [16] from Microsoft Research [17], Eduarda Mendes Rodrigues [18] from the University of Porto [19],  Ben Shneiderman [20], Derek Hansen [21], Cody Dunne [22] and others at the University of Maryland [23], Marc Smith [24] at Connected Action Consulting [25] , Jure Leskovec [26] at Stanford University [27], Vladimir Barash [28] and Scott Golder [29] at Cornell [30], Bernie Hogan [31] at Oxford University [32], and Libby Hemphill [33] at the Illinois Institute of Technology [34].   Recent additions to the Social Media Research Foundation include Han Woo Park from Yeungnam University, GiHong Yi from Hallym University, John Kelly from Morningside Analytics, Itai Himelboim from the University of Georgia, and Alfredo Ferro from the University of Catania.

The Social Media Research Foundation is dedicated to Open Tools, Open Data, and Open Scholarship.

Social media is the term for all the ways people connect to people through computation.  Mobile devices, social networks, micro-blogging and location sharing are just a few of the ways people engage in computer-mediated collective action.

Mapping, measuring and understanding the landscape of social media is our mission.  We support tool projects that enable the collection, analysis and visualization of social media data.  We host data sets that are relevant to social media research.  And we will support graduate students studying and building research related to social media.

Today, in addition to NodeXL we are expanding to include data collection tools for additional social media sources, better support for exploring the changes in networks over time, and web based applications to expand access to network analysis services and insights.
Please help us support the continued development of NodeXL with your donation<https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=J5AERGAAN552S>!  Your contribution<https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=J5AERGAAN552S> will sustain the creation of open tools, open data, and open scholarship!


Marc Smith

Social Media Research Foundation
marc at smrfoundation.org<mailto:marc at smrfoundation.org>

Social Media Research Related Publications
Group-in-a-box Layout for Multi-faceted Analysis of Communities [35]
Eduarda Mendes Rodrigues, Natasa Milic-Frayling, Marc Smith, Ben Shneiderman, Derek Hansen
IEEE Third International Conference on Social Computing, October 9-11, 2011.
Boston, MA
Abstract: Communities in social networks emerge from interactions among individuals and can be analyzed through a  combination of clustering and graph layout algorithms. These approaches result in 2D or 3D visualizations of clustered graphs, with groups of vertices representing individuals that form a community. However, in many instances the vertices have attributes that divide individuals into distinct categories such as gender, profession, geographic location, and similar. It is often important to investigate what categories of individuals comprise each community and vice-versa, how the community structures associate the individuals from the same category. Currently, there are no effective methods for analyzing both the community structure and the category-based partitions of social graphs. We propose Group-In-a-Box (GIB), a metalayout for clustered graphs that enables multi-faceted analysis of networks. It uses the treemap space filling technique to display each graph cluster or category group within its own box, sized according to the number of vertices therein. GIB optimizes visualization of the network sub-graphs, providing a semantic substrate for category-based and cluster-based partitions of social graphs. We illustrate the application of GIB to multi-faceted analysis of real social networks and discuss desirable properties of GIB using synthetic datasets.

EventGraphs: charting collections of conference connections [36]
Hansen, D., Smith, M., Shneiderman, B.
Hawaii International Conference on System Sciences. Forty-Forth Annual Hawaii International Conference on System Sciences (HICSS). January 4-7, 2011. Kauai, Hawaii.

Abstract: EventGraphs are social media network diagrams constructed from content selected by its association with time-bounded events, such as conferences. Many conferences now communicate a common "hashtag" or keyword to identify messages related to the event. EventGraphs help make sense of the collections of connections that form when people follow, reply or mention one another and a keyword. This paper defines EventGraphs, characterizes different types, and shows how the social media network analysis add-in NodeXL supports their creation and analysis. The paper also identifies the structural and conversational patterns to look for and highlight in EventGraphs and provides design ideas for their improvement.

Visualizing the Signatures of Social Roles in Online Discussion Groups [37]
Welser, Howard T., Eric Gleave, Danyel Fisher, and Marc Smith.
Journal of Social Structure, Vol 8. 2007.

Abstract: Social roles in online discussion forums can be described by patterned characteristics of communication between network members which we conceive of as ‘structural signatures.' This paper uses visualization methods to reveal these structural signatures and regression analysis to confirm the relationship between these signatures and their associated roles in Usenet newsgroups. Our analysis focuses on distinguishing the signatures of one role from others, the role of “answer people." Answer people are individuals whose dominant behavior is to respond to questions posed by other users. We found that answer people predominantly contribute one or a few messages to discussions initiated by others, are disproportionately tied to relative isolates, have few intense ties and have few triangles in their local networks. OLS regression shows that these signatures are strongly correlated with role behavior and, in combination, provide a strongly predictive model for identifying role behavior (R2=.72). To conclude, we consider strategies for further improving the identification of role behavior in online discussion settings and consider how the development of a taxonomy of author types could be extended to a taxonomy of newsgroups in particular and discussion systems in general.

Discussion catalysts in online political discussions: Content importers and conversation starters [38]
Himelboim, Itai, Eric Gleave, and Marc Smith. 2009
Journal of Computer-Mediated Communication, Vol. 14 (JCMC)

Abstract: This study addresses 3 research questions in the context of online political discussions: What is the distribution of successful topic starting practices, what characterizes the content of large thread-starting messages, and what is the source of that content? A 6-month analysis of almost 40,000 authors in 20 political Usenet newsgroups identified authors who received a disproportionate number of replies. We labeled these authors ‘‘discussion catalysts.’’ Content analysis revealed that 95 percent of discussion catalysts’ messages contained content imported from elsewhere on the web, about 2/3 from traditional news organizations. We conclude that the flow of information from the content creators to the readers and writers continues to be mediated by a few individuals who act as filters and amplifiers.

Analyzing (Social Media) Networks with NodeXL [39]
Smith, M., Shneiderman, B., Milic-Frayling, N., Rodrigues, E.M., Barash, V., Dunne, C., Capone, T., Perer, A. & Gleave, E. (2009)
C&T '09: Proceedings of the Fourth International Conference on Communities and Technologies. Springer.

Abstract: In this paper we present NodeXL, an extendible toolkit for network data analysis and visualization, implemented as an add-in to the Microsoft Excel 2007 spreadsheet software. We demonstrate NodeXL features through analysis of a data sample drawn from an enterprise intranet social network, discussion, and wiki. Through a sequence of steps we show how NodeXL leverages and extends the broadly used spreadsheet paradigm to support common operations in network analysis. This ranges from data import to computation of network statistics and refinement of network visualization through a selection of ready-to-use sorting, filtering, and clustering functions.

Whither the experts: Social affordances and the cultivation of experts in community Q&A systems [40]
SIN '09: Proc. international symposium on Social Intelligence and Networking. IEEE Computer Society Press.
Howard Welser, Eric Gleave, Marc Smith, Vladimir Barash, Jessica Meckes.

Abstract: Community based Question and Answer systems have been promoted as web 2.0 solutions to the problem of finding expert knowledge. This promise depends on systems’ capacity to attract and sustain experts capable of offering high quality, factual answers. Content analysis of dedicated contributors’ messages in the Live QnA system found: (1) few contributors who focused on providing technical answers (2) a preponderance of attention paid to opinion and discussion, especially in non-technical threads. This paucity of experts raises an important general question: how do the social affordances of a site alter the ecology of roles found there? Using insights from recent research in online community, we generate a series of expectations about how social affordances are likely to alter the role ecology of online systems.

First steps to NetViz Nirvana: evaluating social network analysis with NodeXL [41]
SIN '09: Proc. international symposium on Social Intelligence and Networking. IEEE Computer Society Press.
Bonsignore, E.M., Dunne, C., Rotman, D., Smith, M., Capone, T., Hansen, D.L. & Shneiderman, B. (2009)

Abstract: Social Network Analysis (SNA) has evolved as a popular, standard method for modeling meaningful, often hidden structural relationships in communities. Existing SNA tools often involve extensive pre-processing or intensive programming skills that can challenge practitioners and students alike. NodeXL, an open-source template for Microsoft Excel, integrates a library of common network metrics and graph layout algorithms within the familiar spreadsheet format, offering a potentially low-barrier to-entry framework for teaching and learning SNA. We present the preliminary findings of 2 user studies of 21 graduate students who engaged in SNA using NodeXL. The majority of students, while information professionals, had little technical background or experience with SNA techniques. Six of the participants had more technical backgrounds and were chosen specifically for their experience with graph drawing and information visualization. Our primary objectives were (1) to evaluate NodeXL as an SNA tool for a broad base of users and (2) to explore methods for teaching SNA. Our complementary dual case-study format demonstrates the usability of NodeXL for a diverse set of users, and significantly, the power of a tightly integrated metrics/visualization tool to spark insight and facilitate sensemaking for students of SNA.

Do You Know the Way to SNA?: A Process Model for Analyzing and Visualizing Social Media Data [42]
Hansen, D., Rotman, D., Bonsignore, E., Milic-Frayling, N., Rodrigues, E., Smith, M., Shneiderman, B. (July 2009)
University of Maryland Tech Report: HCIL-2009-17

Abstract: Voluminous online activity data from users of social media can shed light on individual behavior, social relationships, and community efficacy. However, tools and processes to analyze this data are just beginning to evolve. We studied 15 graduate students who were taught to use NodeXL to analyze social media data sets. Based on these observations, we present a process model of social network analysis (SNA) and visualization, then use it to identify stages where intervention from peers, experts, and computational aids are most useful. We offer implications for designers of SNA tools, educators, and community & organizational analysts.



[1] NodeXL: http://www.codeplex.com/nodexl
[2] Social Media Research Foundation: http://www.smrfoundation.org/
[3] NodeXL Tech Support: http://nodexl.codeplex.com/Thread/List.aspx
[4] NodeXL Image Gallery: http://www.flickr.com/photos/marc_smith/sets/72157622437066929/
[5] NodeXL News and Blog: http://www.connectedaction.net/
[6] NodeXL: Talk: http://www.connectedaction.net/2010/06/04/june-3-and-4-2010-personal-democracy-forum-2010-nyc/
[7] NodeXL Video: http://www.connectedaction.net/2009/11/11/video-using-nodexl-to-map-the-digg-mentioning-twitter-population/
[8] NodeXL Tutorial: http://casci.umd.edu/images/4/46/NodeXL_tutorial_draft.pdf
[9] UMD CASCI: http://casci.umd.edu/NodeXL_Teaching
[10] NodeXL Book: http://www.amazon.com/gp/product/0123822297?ie=UTF8&tag=conneactio-20&linkCode=as2&camp=1789&creative=390957&creativeASIN=0123822297
[11] NodeXL Slides: http://www.slideshare.net/Marc_A_Smith/2009-december-nodexl-overview
[12] NodeXL Slides: http://www.slideshare.net/Marc_A_Smith/2010-june-personal-democracy-forum-marc-smith-mapping-political-social-media-crowds
[13] NodeXL Video: http://www.connectedaction.net/2010/06/04/june-3-and-4-2010-personal-democracy-forum-2010-nyc/
[14] Uberlink's NodeXL + VOSON: http://www.uberlink.com.au/
[15] Microsoft Research Connections: http://research.microsoft.com/en-us/collaboration/
[16] Natasa Milic-Frayling: http://research.microsoft.com/en-us/people/natasamf/
[17] Microsoft Research: http://research.microsoft.com/
[18] Eduarda Mendes Rodrigues: http://www.fe.up.pt/si_uk/FUNCIONARIOS_GERAL.FORMVIEW?p_codigo=466635
[19] University of Porto: http://www.fe.up.pt/
[20] Ben Shneiderman: http://www.cs.umd.edu/~ben/<http://www.cs.umd.edu/%7Eben/>
[21] Derek Hansen: http://ischool.umd.edu/people/hansen/
[22] Cody Dunne: http://www.cs.umd.edu/~cdunne/<http://www.cs.umd.edu/%7Ecdunne/>
[23] University of Maryland: http://www.umd.edu/
[24] Marc Smith: http://www.connectedaction.net/marc-smith/
[25] Connected Action: http://www.connectedaction.net/
[26] Jure Leskovec: http://cs.stanford.edu/people/jure/
[27] Stanford University: http://cs.stanford.edu/
[28] Vladimir Barash: http://www.vlad43210.com/
[29] Scott Golder: http://www.redlog.net/
[30] Cornell University: http://www.cornell.edu/
[31] Bernie Hogan: http://www.oii.ox.ac.uk/people/?id=140
[32] Oxford Internet Institute: http://www.oii.ox.ac.uk/
[33] Libby Hemphill: http://www.libbyh.com/
[34] Illinois Institute of Technology: http://www.iit.edu/
[35] Group-in-a-box: http://www.connectedaction.net/2011/10/10/october-9-11-2011-ieee-2011-social-computing-boston-nodexl-paper-on-group-in-a-box-layouts/
[36] EventGraphs: http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2010-13
[37] Visualizing Signatures: http://www.cmu.edu/joss/content/articles/volume8/Welser/
[38] Discussion catalysts: http://jcmc.indiana.edu/ at http://ping.fm/7NF5T
[39] Analyzing (social media) networks: http://www.connectedaction.net/wp-content/uploads/2009/08/2009-CT-NodeXL-and-Social-Queries-a-social-media-network-analysis-toolkit.pdf
[40] Whither the Experts: http://www.connectedaction.net/wp-content/uploads/2009/08/2009-Social-Computing-Whither-the-Experts.pdf
[41] NetViz Nirvana: http://www.cs.umd.edu/~cdunne/pubs/Bonsignore09Firststepsto.pdf<http://www.cs.umd.edu/%7Ecdunne/pubs/Bonsignore09Firststepsto.pdf>
[42] The way to SNA: http://hcil.cs.umd.edu/trs/2009-17/2009-17.pdf

Shelia R. Cotten, PhD
Department of Sociology
University of Alabama, Birmingham
460N Heritage Hall
1530 3rd Ave S.
Birmingham, AL 35294-1152
cotten at uab.edu
Chair, Communication and Information Technologies Section (CITASA), American Sociological Association
Twitter: @shelia_cotten

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