#JW11 NodeXL SNA Map for 10 October 2011

11OctMay 7, 2015 By Marc Smith

The Jive World 11 conference took place October 4-6, 2011.

[flickr id=”6234653454″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]
These are the connections among the Twitter users who recently tweeted the word #JW11 when queried on October 10, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

See: www.jivesoftware.com/jiveworld

A larger version of the image is here: www.flickr.com/photos/marc_smith/6234653454/sizes/l/in/ph…

Top most between users:
@jivesoftware
@gialyons
@mikefraietta
@cflanagan
@cosmopolitan_lv
@ginorossi
@kristinhersant
@thebrandbuilder
@alanlepo
@mor_trisha

Graph Metric: Value
Graph Type: Directed
Vertices: 345
Unique Edges: 3606
Edges With Duplicates: 2072
Total Edges: 5678
Self-Loops: 632
Connected Components: 11
Single-Vertex Connected Components: 9
Maximum Vertices in a Connected Component: 334
Maximum Edges in a Connected Component: 5659
Maximum Geodesic Distance (Diameter): 5
Average Geodesic Distance: 2.353001
Graph Density: 0.034184361
NodeXL Version: 1.0.1.179

More NodeXL network visualizations are here: www.flickr.com/photos/marc_smith/sets/72157622437066929/

WIN 2011 NodeXL SNA Twitter Map

03OctMay 7, 2015 By Marc Smith

The Workshop on Information in Networks 2011 was held at NYU September 30-October 1st.

Over the course of the event a number of people tweeted using the hashtag #win2011.

[flickr id=”6209064926″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]
These are the connections among the Twitter users who recently tweeted the word win2011 when queried on October 3, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

See: winworkshop.net/

Layout using the “Group Layout” composed of tiled bounded regions. Clusters calculated by the Clauset-Newman-Moore algorithm are also encoded by color.

A larger version of the image is here:http://www.flickr.com/photos/marc_smith/6209064926/sizes/l/in/photostream/

Betweenness Centrality is defined here: en.wikipedia.org/wiki/Centrality#Betweenness_centrality

Clauset-Newman-Moore algorithm is defined here: pre.aps.org/abstract/PRE/v70/i6/e066111

Top most between users:

@sinanaral
@winworkshop
@barrywellman
@ladamic
@seanjtaylor
@drewconway
@chrisdiehl
@dylanwalker
@marc_smith
@ariegoldshlager

Graph Metric: Value
Graph Type: Directed
Vertices: 38
Unique Edges: 227
Edges With Duplicates: 193
Total Edges: 420
Self-Loops: 68
Connected Components: 1
Single-Vertex Connected Components: 0
Maximum Vertices in a Connected Component: 38
Maximum Edges in a Connected Component: 420
Maximum Geodesic Distance (Diameter): 3
Average Geodesic Distance: 1.836565
Graph Density: 0.194167852
NodeXL Version: 1.0.1.179

[flickr id=”6198785387″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]

These are the connections among the Twitter users who tweeted the word win2011 when queried a few days earlier on September 30, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

A larger version of the image is here: www.flickr.com/photos/marc_smith/6198785387/sizes/l/in/ph…

Top most between users:
Continue reading →

WikiSym NodeXL SNA Map 3 October 2011

03OctMay 7, 2015 By Marc Smith

WikiSym 2011, the conference on Wiki and open collaboration research took place October 3-5 in Mountain View, California.

At the end of the conference on October 5th, the network of connections among the people who tweeted about Wikisym looked like this:

[flickr id=”6216434818″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]

These are the connections among the Twitter users who recently tweeted the word wikisym when queried on October 5, 2011, scaled by numbers of followers (with outliers thresholded). Connections are created when users reply, mention or follow one another.

See: www.wikisym.org/

Top most between users:
@edchi
@jfelipe
@phauly
@readermeter
@hfordsa
@wikisym
@clifflampe
@staeiou
@geoplace
@wikimedia

Graph Metric: Value
Graph Type: Directed
Vertices: 170
Unique Edges: 1163
Edges With Duplicates: 2165
Total Edges: 3328
Self-Loops: 658
Connected Components: 5
Single-Vertex Connected Components: 3
Maximum Vertices in a Connected Component: 165
Maximum Edges in a Connected Component: 3319
Maximum Geodesic Distance (Diameter): 6
Average Geodesic Distance: 2.385502
Graph Density: 0.052941176
NodeXL Version: 1.0.1.179

In contrast, a few days earlier, these are the connections among the Twitter users who recently tweeted the word wikisym when queried on October 3, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

[flickr id=”6208023177″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]

Top most between users:
@wikisym
@jfelipe
@andicat
@geoplace
@staeiou
@dirkriehle
@wikimedia
@edchi
@bkeegan
@hfordsa

Graph Metric: Value
Graph Type: Directed
Vertices: 78
Unique Edges: 459
Edges With Duplicates: 354
Total Edges: 813
Self-Loops: 132
Connected Components: 10
Single-Vertex Connected Components: 8
Maximum Vertices in a Connected Component: 68
Maximum Edges in a Connected Component: 800
Maximum Geodesic Distance (Diameter): 5
Average Geodesic Distance: 2.207506
Graph Density: 0.086913087
NodeXL Version: 1.0.1.179

More NodeXL network visualizations are here: www.flickr.com/photos/marc_smith/sets/72157622437066929/

NodeXL is free and open and available from www.codeplex.com/nodexl

NodeXL is developed by the Social Media Research Foundation (www.smrfoundation.org) – which is dedicated to open tools, open data, and open scholarship.

The book, Analyzing social media networks with NodeXL: Insights from a connected world, is available from Morgan Kaufmann and from Amazon.

Marc Smith on Twitter.

Strata Conf: Mapping the connections among Twitter Users

02OctMay 7, 2015 By Marc Smith

The recent Strata Conference in New York City gathered many leaders in big data, data mining, and information visualization.

[flickr id=”6203313170″ thumbnail=”medium” overlay=”true” size=”large” group=”” align=”none”]

Link: www.flickr.com/photos/marc_smith/6203313170

Connections among the Twitter users who recently tweeted the word Strata when queried on September 20, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

See: strataconf.com/summit2011

Layout using the “Group Layout” composed of tiled bounded regions. Clusters calculated by the Clauset-Newman-Moore algorithm are also encoded by color.

A larger version of the image is here: www.flickr.com/photos/marc_smith/6203313170/sizes/l/in/ph…

Betweenness Centrality is defined here: en.wikipedia.org/wiki/Centrality#Betweenness_centrality

Clauset-Newman-Moore algorithm is defined here: pre.aps.org/abstract/PRE/v70/i6/e066111

Top most between users:
@timoreilly
@strataconf
@doctorow
@acroll
@ticbeat
@datacenter
@hnshah
@oreillymedia
@markmadsen
@unglobalpulse

Graph Metric: Value
Graph Type: Directed
Vertices: 1118
Unique Edges: 5813
Edges With Duplicates: 6522
Total Edges: 12335
Self-Loops: 1010
Connected Components: 9
Single-Vertex Connected Components: 8
Maximum Vertices in a Connected Component: 1110
Maximum Edges in a Connected Component: 12327
Maximum Geodesic Distance (Diameter): 6
Average Geodesic Distance: 2.575622
Graph Density: 0.00647018
NodeXL Version: 1.0.1.177

More NodeXL network visualizations are here: www.flickr.com/photos/marc_smith/sets/72157622437066929/
NodeXL is free and open and available from www.codeplex.com/nodexl
NodeXL is developed by the Social Media Research Foundation (www.smrfoundation.org) – which is dedicated to open tools, open data, and open scholarship.
The book, Analyzing social media networks with NodeXL: Insights from a connected world, is available from Morgan Kaufmann and from Amazon.

Please vote on our SxSW panel: Social Mapping: Bridging Online & Offline Events

15AugMay 7, 2015 By Marc Smith

Please vote on our SxSW 2012 panel:

Social Mapping : Bridging Online & Offline Events
Event	Interactive 2012
Format	Workshop
Organizer	Emily Gannett ‐ IRL Productions
Speakers	Marc Smith ‐ Social Media Research Foundation
Description	Look up from your phone and you will notice that offline is not obsolete. Experiences in real life (IRL) remain powerful and memorable. Online tools and social platforms are now thoroughly integrated into “offline” life on smart devices in every meeting, conference, or gathering. Marketers can now tie online and offline activity together, mapping online discussions and offline connections to spur awareness, connections, and lasting conversations. Featuring insight from the Social Media Research Foundation and case studies from some of the world’s top brands, this intermediate workshop will teach techniques for integrating social media and emerging technologies with events and experiential marketing campaigns. We’ll illustrate free and open tools for collecting, analyzing and visualizing patterns of how people engage with your topic using various social media channels like Facebook, Twitter and Foursquare. We will review how to augment face-to-face interactions, and present case studies of interactive events that fit cohesively into established online and offline marketing campaigns. Maps of the connections that form when people communicate can reveal the key people and groups who act as your brand influencers. Learn how to make maps of your own, with no programming skills required, to guide your own engagement with stakeholders, online and off.
Questions Answered	How can marketers leverage digital media to increase the value of experiential marketing? How can they create breadth and impact beyond the transaction? What are the best new platforms and tools to leverage? What was your favorite integrated campaign this year? Which brands did an excellent job of incorporating social media at events and weaving digital throughout? What social media data can be collected at events and conferences? What can you do to better understand your customers through this information? What are the best ways to compare online and offline metrics? Do we need new standards?
Level	Intermediate
Category	Branding / Marketing / Advertising
Tags	Events, Metrics, social media

Thanks for your vote for our SxSW panel!

May 28/29 Quantified Self 2011 – Conference in Mountain View, California, NodeXL EventGraph Maps of #quantifiedself

25MayMay 7, 2015 By Marc Smith

I am very interested in the Quantified Self conference to be held in Mountain View, California, May 28 and 29. While I have attended just a few of the in-person meet-ups, which were engaging and intriguing events, I have followed the blog and tweet stream closely. These events feature short presentations about practices, prototypes, and products that record information about our own behavior and activity. It is great to hear that, as the meet-ups grew to become very large, a conference has been organized to accommodate the demand and growing interest in the intersection of sensors and other devices with medical and personal self-monitoring. Using a variety of devices, our lives can now create detailed inscriptions that illuminate our behavior and patterns with novel clarity and detail. (See: http://quantifiedself.com/conference/)

I plan to attend. I will speak on Sunday morning at a 10:30 breakout session on using social media network analysis to map personal and collective social media spaces.

Quantifying the “Quantified Self” discussion in Twitter: Here is a map of the connections among the people who recently tweeted the string “quantified self” on May 25th, 2011.

[flickr id=”5760875146″ thumbnail=”medium” overlay=”true” size=”medium” group=”” align=”none”]
Click for larger image.

The top most between participants in this graph were:
[flickr id=”5760331211″ thumbnail=”medium” overlay=”true” size=”medium” group=”” align=”none”]
@timoreilly
@quantifiedself (-1)
@harscoat (-)
@edyson
@qsparis
@egadenne (-4)
@agaricus (-)
@brunoaziza
@adriana872
@chloester

Bolded users also appeared in a previous map made earlier in the year, on January 20, 2011, which looked like this:

This is the list of the most “between” users in this network on January 20th, 2011:

The most between participants in this graph are: @quantifiedself, @egadenne, @harscoat, @genomera, @neufit, @jxa, @agaricus, @emergentorder, @bulletproofexec, @2healthguru.

The topics discussed in the quantifiedself tweet stream can be rendered as a network graph based on words that co-occur:

[flickrset id=”72157626748710875″ thumbnail=”thumbnail” photos=”” overlay=”false” size=”small”]

NodeXL EventGraph: ACM CHI2011 – Twitter Connections

08MayMay 7, 2015 By Marc Smith

The ACM CHI 2011 Conference is taking place in Vancouver, BC.

May 10, 2011

May 8, 2011

These are the connections among the Twitter users who recently tweeted the word chi2011 when queried on May 8, 2011, scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

Layout using the “Group Layout” composed of tiled bounded regions. Clusters calculated by the Clauset-Newman-Moore algorithm are also encoded by color.

A larger version of the network map is here: www.flickr.com/photos/marc_smith/5701022497/sizes/o/in/ph…

Top most between users:
@chi2011
@msftresearch
@edchi
@jeffbigham
@landay
@evanmpeck
@acagamic
@clifflampe
@yardi
@eytanadar

Graph Metric: Value
Graph Type: Directed
Vertices: 421
Unique Edges: 3849
Edges With Duplicates: 324
Total Edges: 4173
Self-Loops: 0
Connected Components: 32
Single-Vertex Connected Components: 29
Maximum Vertices in a Connected Component: 384
Maximum Edges in a Connected Component: 4146
Maximum Geodesic Distance (Diameter): 6
Average Geodesic Distance: 2.553249
Graph Density: 0.022587943

NodeXL Version1.0.1.167

Data set in NodeXL format.

NodeXL is free and open and available from www.codeplex.com/nodexl

NodeXL is developed by the Social Media Research Foundation (www.smrfoundation.org) – which is dedicated to open tools, open data, and open scholarship.

Paper: Tech Report at University of Maryland on EventGraphs

08JulMay 7, 2015 By Marc Smith

A new paper on visualizing social media has been released on the University of Maryland, Human Computer Interaction Laboratory tech report archive. Co-authored by Derek Hansen, myself, and Ben Shneiderman, the paper describes and visualizes the patterns of connections formed when people tweet about events like conferences and news stories.

EventGraphs_2010_HCIL_Tech_Report

http://www.cs.umd.edu/localphp/hcil/tech-reports-search.php?number=2010-13

Hansen, D., Smith, M., Shneiderman, B.
EventGraphs: Charting Collections of Conference Connections
HCIL-2010-13

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.

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