I will speak this March 4th at the 2012 Predictive Analytics World in San Francisco about ” Crowd Photography for Social Media“.

http://www.predictiveanalyticsworld.com/sanfrancisco/2012/speakers.php
http://www.predictiveanalyticsworld.com/sanfrancisco/2012/agenda.php#

Monday @ 5:25-5:45pm

Track 1:
Social Data Case Study:
Social Media Research Foundation
Crowd Photography for Social Media

Crowds of people gather in social media around many products, services, businesses, and events but they can be difficult to see and understand. With new free and open tools, it is now possible to map and measure social media spaces, capturing the sub-groups and key people within and between them. Learn how to capture social media data and quickly generate a visual map of the crowd. With maps in hand, we will discuss ways they guide a journey to the key influencers and concepts in the crowd.

Speaker: Marc Smith, Director, Social Media Research Foundation

Mapping social media networks (with no coding) using NodeXL

Time: 16:50 on 01 Mar 2012.

Session type: 40 minute presentation

Topics: Visualization & Interface

Description: Maps of the complex connections that form when people link, like, reply, rate, review, favorite, friend, follow, edit, and mention one another can reveal important trends. It is possible to create network maps with free and open tools that identify key people and sub-groups in any social media population with just a few key clicks. Can you make a pie chart? You can now make a network chart.

Abstract: Networks are a data structure common found across all social media services that allow populations to author collections of connections. The Social Media Research Foundation’s (http://www.smrfoundation.org) free and open NodeXL project (http://nodexl.codeplex.com) makes analysis of social media networks accessible to most users of the Excel spreadsheet application. With NodeXL, Networks become as easy to create as pie charts. Applying the tool to a range of social media networks has already revealed the variations present in online social spaces. A review of the tool and images of Twitter, flickr, YouTube, and email networks will be presented.

We now live in a sea of tweets, posts, blogs, and updates coming from a significant fraction of the people in the connected world. Our personal and professional relationships are now made up as much of texts, emails, phone calls, photos, videos, documents, slides, and game play as by face-to-face interactions. Social media can be a bewildering stream of comments, a daunting fire hose of content. With better tools and a few key concepts from the social sciences, the social media swarm of favorites, comments, tags, likes, ratings, and links can be brought into clearer focus to reveal key people, topics and sub-communities. As more social interactions move through machine-readable data sets new insights and illustrations of human relationships and organizations become possible. But new forms of data require new tools to collect, analyze, and communicate insights.

I will present a talk at Personal Digital Archiving 2012 titled “Arc-chiving: saving social links for study“.

The conference will be held on Thursday-Friday, February 23-24, 2012 at the Internet Archive in San Francisco.

News and updates on the conference will be posted at the conference web site, http://personalarchiving.com.

My talk this year will focus on collecting and analyzing connections between digital objects (like users) and the insights these tools make possible.

Abstract: While digital content is archived in various ways, the “arcs” or links among people and their digital objects are not systematically saved. Efforts to store social media often overlooks including data about collections of connections. The Social Media Research Foundation is dedicated to open tools, open data, and open scholarship related to social media. It is producing tools that can collect, analyze and upload social media data, including the arcs that link people and objects. Using the free and open NodeXL application, users can collect, analyze and visualize complex networks and then upload the data to a growing archive on the web at NodeXLGraphGallery.org. As the group of researchers grows, an archive is being assembled to provide researchers around the world with the data about social media needed to understand the ways computer mediated communication tools shape society.

My talk at the 2011 Personal Digital Archiving conference is available through the Internet Archive’s video service:

I will speak at the International Symposium on Convergence Technology (ConTech 2011) – Smart & Humane World – on November 3rd in Seoul, South Korea.

Date: 2011 November 3 (Thurs)
Place: COEX Grand Ballroom, Seoul, Korea
Organized by Advanced Institutes of Convergence Technologies (AICT), Seoul National University (SNU)
In Cooperation with Ministry of Knowledge Economy, Ministry of Education, Science and Technology, National Research Foundation of Korea, Graduate School of Convergence Science and Technology (GSCST)
Symposium Chair : Choi, Yanghee (President, AICT)

Program
09:00~09:30 Registration
09:30~10:00 Opening Ceremony
Plenary Session : Smart & Humane World through Convergence
10:00~10:40 Speaker (TBD)
10:50~11:30 Speaker (TBD)
11:30~13:00 Lunch
Session 1 : Bio Convergence (Chair : Prof. Kim, Sunghoon)
Session 2 : IT Convergence (Chair : Dr. Lee, Manjai)
Session 3 : Appropriate Technology (Chair : Prof. Kang, Namjun)
13:00~15:00 Scott A. Strobel (Professor, Yale University)
Speaker Kevin Kim (Professor, University of Illinois)
Speaker Masaru Kitsuregawa (Professor, Tokyo University)
Speaker Haesun Park (Professor, Georgia Institute of Technology)
Speaker Marc Smith (Connected Action)
Speaker Sang-goo Lee (Professor, Seoul National University)
Speaker Haklae Kim (Samsung)
Speaker Raghu Ramakrishnan (Yahoo)

My slides: 20111103 con tech2011-marc smith

I will also visit Professor Han Woo Park at YeungNam University (Wikipedia) in Daegu, South Korea to meet with his students in the Webometrics Institute program.

This will be my second trip to Korea, I was there last year for a related event.  Pictures after the jump:

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/

This year the IEEE Social Computing conference is being held in Boston, October 9-11, 2011.

The NodeXL team from the Social Media Research Foundation have a paper on our newest layout feature in NodeXL: Group-in-a-box.

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.

The paper is authored by:

Eduarda Mendes Rodrigues*, Natasa Milic-Frayling†, Marc Smith‡, Ben Shneiderman§, Derek Hansen¶
* Dept. of Informatics Engineering, Faculty of Engineering, University of Porto, Portugal – eduardamr @ acm.org
† Microsoft Research, Cambridge, UK -natasamf @ microsoft.com
‡ Connected Action Consulting Group, Belmont, California, USA – marc @ connectedaction.net
§ Dept. of Computer Science & Human-Computer Interaction Lab, University of Maryland, College Park, Maryland, USA – ben @ cs.umd.edu
¶ College of Information Studies, University of Maryland, College Park, Maryland – dlhansen @ umd.edu

A map of the connections among the people who recently tweeted #SocialCom2011:

Connections among the Twitter users who recently tweeted the word #socialcom2011 when queried on October 10, 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 image is here: www.flickr.com/photos/marc_smith/6232130442/sizes/l/in/ph…

Top most between users:
@danielequercia
@gadgetman4u
@bkeegan
@shaunlawson
@maryheston
@mmiiina
@ronaldomenezes
@theshadowhost
@fergal_reid
@cosleydr

Graph Metric: Value
Graph Type: Directed
Vertices: 36
Unique Edges: 119
Edges With Duplicates: 155
Total Edges: 274
Self-Loops: 105
Connected Components: 2
Single-Vertex Connected Components: 1
Maximum Vertices in a Connected Component: 35
Maximum Edges in a Connected Component: 273
Maximum Geodesic Distance (Diameter): 5
Average Geodesic Distance: 2.174551
Graph Density: 0.107936508
NodeXL Version: 1.0.1.179

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

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

Top most between users:
@benioff
@oracleopenworld
@salesforce
@arstechnica
@sai
@oracledatabase
@sapjobswithace
@kirbylunger
@capgemini
@reuters_biz

Graph Metric: Value
Graph Type: Directed
Vertices: 1000
Unique Edges: 2747
Edges With Duplicates: 827
Total Edges: 3574
Self-Loops: 1102
Connected Components: 425
Single-Vertex Connected Components: 396
Maximum Vertices in a Connected Component: 541
Maximum Edges in a Connected Component: 2923
Maximum Geodesic Distance (Diameter): 10
Average Geodesic Distance: 3.475208
Graph Density: 0.00226026
NodeXL Version: 1.0.1.179

A related map represents the connections among people who tweeted the term #OOW11

These are the connections among the Twitter users who recently tweeted the word oow11 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: www.oracle.com/openworld/live/on-demand/index.html

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:
@oracleopenworld
@oracle
@oracletechnet
@rwang0
@devops_borat
@salesforce
@mysql
@emcoracle
@oraclemix
@oracledatabase

Graph Metric: Value
Graph Type: Directed
Vertices: 670
Unique Edges: 5882
Edges With Duplicates: 1573
Total Edges: 7455
Self-Loops: 881
Connected Components: 45
Single-Vertex Connected Components: 44
Maximum Vertices in a Connected Component: 626
Maximum Edges in a Connected Component: 7405
Maximum Geodesic Distance (Diameter): 7
Average Geodesic Distance: 2.770009
Graph Density: 0.013401602
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 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.

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

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:
@sinanaral
@winworkshop
@ariegoldshlager
@drewconway
@chrisdiehl
@kateaanderson
@dylanwalker
@barrywellman
@kristinalerman
@pboothe

Graph Metric: Value
Graph Type: Directed
Vertices: 16
Unique Edges: 60
Edges With Duplicates: 45
Total Edges: 105
Self-Loops: 26
Connected Components: 1
Single-Vertex Connected Components: 0
Maximum Vertices in a Connected Component: 16
Maximum Edges in a Connected Component: 105
Maximum Geodesic Distance (Diameter): 3
Average Geodesic Distance: 1.617188
Graph Density: 0.270833333
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.

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

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.

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.

I have enjoyed and been educated by my previous visits to South Africa and the Mobile Web in Africa conference, now in its 3rd year.

MWA gathers the many parts of the picture of mobile technologies in play across the African continent.

I will speak again at this year’s event, focusing on social media networks.  My partner is Walter Pike, a marketing professional with a specialty in digital media.

Here is the agenda for the workshop on Friday, November 25th.

Photos from the prior two years of Mobile Web Africa after the jump:

2010

2009

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

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.

Summer Social Webshop
on
Technology-Mediated Social Participation
University of Maryland, College Park
August 23-26, 2011

Eventful.  The 2011 Webshop at the University of Maryland was certainly that with both an earthquake and a hurricane to mark the start and end of the event.  We really moved heaven and earth at this workshop.

In 4  days, 20 talks, 45 students, an earthquake, a hurricane and many new connections – the Webshop touched on a set of related concepts, methods, and findings about ways to use communication and computation technology to help groups, neighborhoods, cities, states, and nations work collectively towards common goals.

Several years ago a program at the University of Maryland called “Webshop” (Web Workshop) was organized by Professor John Robinson and held for three consecutive Summers.  I visited and spoke at two of these events and know many people who attended or spoke at one or more and remember the event enthusiastically.   The students who attended include some of the now leading researchers in the field of social science studies of the internet.  There is an impressive alumni list.

The last Webshop was held in 2003 and many years and significant changes have occurred in the time since. Twitter, Facebook, StreetView, iPad,FourSquare, Android, Kinect, EC2, Mechanical Turk, Arduino, were all new or non-existent when the first Webshops were run.  Today we have more reason than ever to focus on the details and patterns of computer-mediated human association. Ever more people channel more of their communications with others through more digital media, often of the social kind.  A new data resource for the social sciences is growing in scale and promise: from billions of events it is possible to start to build a picture of an aggregate whole, and to start to grasp the terrain and landscape of social media.

After many years of inactivity, the Summer Social Webshop (@Webshop2011) happened again!  With the generous support of the National Science Foundation and additional assistance from Google Research, on August 23-26, 2011 at the University of Maryland, College Park, a group of students heard and engaged with more than two dozen leading researchers exploring digital social landscapes from a variety of perspectives.  Organized by a collaboration between the University of Maryland’s Human Computer Interaction Laboratory (HCIL), the College of Information Studies, the Sociology and Computer Science Department, and the Social Media Research Foundation, the event gathered students from a wide range of disciplines to get a concentrated dose of advanced efforts to gather data from social media and people’s understanding and practices around digital technologies.   Doctoral students in computer science, iSchools, sociology, communications, political science, anthropology, psychology, journalism, and related disciplines applied to attend the 4-day intensive workshop on Technology-Mediated Social Participation (TMSP).  The workshop explored the many ways social media can be applied to national priorities such as health, energy, education, disaster response, political participation, environmental protection, business innovation, or community safety.  The workshop attracted graduate students at US universities studying social-networking tools, blogs and microblogs, user-generated content sites, discussion groups, problem reporting, recommendation systems, mobile and location aware media creation, and other social media.

-

Organizers

Alan Neustadtl (@smilex3md) - Sociology, University of Maryland
Jennifer Preece (@jenpre) – iSchool, University of Maryland
Marc Smith(@Marc_Smith) - Social Media Research Foundation
Ben Shneiderman (@benbendc) - Computer Science, University of Maryland
PJ Rey (@pjrey) - Sociology, University of Maryland, Student Coordinator

-

Photos

Here is a map of the connections among the people who tweeted the term “AEJMC” on August 7, 2011:

The top most between people in this network are:@aejmc, @jlab, @karenrussell, @terryflynn, @natcomm, @tmccorkindale, @derigansilver, @tkell, @aejmconlineads, and @jeremyhl:

I will present a Workshop on Social Media Network Analysis and NodeXL at the 9 August 2011 – Association for Education in Journalism and Mass Communication (http://www.aejmc.com) in St. Louis, Missouri along with my colleague Professor Hernando Rojas, from the School of Journalism & Mass Communication, University of Wisconsin – Madison.

See: http://www.aejmc.com/home/events/annual-convention/

The Association for Education in Journalism and Mass Communication (AEJMC) is a nonprofit, educational association of journalism and mass communication educators, students and media professionals. The Association’s mission is to promote the highest possible standards for journalism and mass communication education, to cultivate the widest possible range of communication research, to encourage the implementation of a multi-cultural society in the classroom and curriculum, and to defend and maintain freedom of communication in an effort to achieve better professional practice and a better informed public.

Our session is:

Using NodeXL for Social Network Analysis
Tuesday — 2 pm to 5 pm
Presented by Communication Theory and Methodology Division
This pre-conference workshop examines social network analysis. Social network analysis can be used to examine message boards, blogs, and friend networks (amongmany other phenomena). Participants will learn to use the NodeXL program to conduct a network analysis. For information, contact Michel M. Haigh, Pennsylvania State University at mmh25@psu.edu.

On June 22nd in New York City Wired Magazine and the Economist hosted a day of discussions and displays related to the theme of “Nextwork” hosted by Juniper Networks and located at the Tribeca Rooftop.

The Social Media Research Foundation displayed and printed  Nextwork Networks maps of the connections among the people who tweeted about the conference, the speakers, and their companies.

Visit the NextWork Network booth hosted by the Social Media Research Foundation to see a map of the connections among people who tweeted the term “NextWork“.  Networks are important data structures but the tools to access, analyze and visualize networks have been hard to use.  New tools now make networks as easy to handle as making a pie chart.  NodeXL, the free and open network overview, discovery and exploration add-in for the familiar Excel spreadsheet, makes creating network diagrams and gaining insights much simpler (see: http://nodexl.codeplex.com).  Using NodeXL, we have been collecting all the tweets that mention the NextWork event and building a network map of the ways those people connect to one another.  Not everyone is equally connected: some people occupy more strategic locations in the web of connections than others.   Find out who: request your own NodeXL social media network map for your Twitter account or the name of your company or brand (or your competitors) by dropping by the booth (or visit: http://www.smrfoundation.org/nextwork2011).

Here is an example, a map of the connections among the people who recently tweeted the name “Kevin Kelly”, one of the speakers at the event:

This is a map of the connections among the people who tweeted the term “Nextwork”:

29 June – 2 July 2011
Queensland University of Technology

Tweet with the hashtag #ct2011

http://ct2011.urbaninformatics.net/

C&T 2011 OVERVIEW

The biennial Communities and Technologies (C&T) conference is the premier international forum for stimulating scholarly debate and disseminating research on the complex connections between communities – both physical and virtual – and information and communication technologies.

C&T 2011 welcomes participation from researchers, designers, educators, industry, and students from the many disciplines and perspectives bearing on the interaction between community and technology, including architecture, arts, business, design, economics, education, engineering, ergonomics, information technology, geography, health, humanities, law, media and communication studies, and social sciences. The conference program will include competitively selected, peer-reviewed papers, as well as pre-conference workshops, a doctoral consortium, and invited keynote and panel speakers.

Marcus Foth
Conference Chair

IMPORTANT DATES
30 April 2011: Workshop papers, Doctoral Consortium and Student Volunteer applications due
29 June 2011: Pre-conference workshops and Doctoral Consortium
30 June – 2 July 2011: C&T 2011 conference at QUT, Brisbane, Australia

CONFERENCE TOPICS

C&T 2011 welcomes contributions in all areas of community and technology research, design and development. In addition, we particularly invite authors to address any of the following topics:

Augmented Reality
Civic Intelligence
Context and Location Awareness
Community-centred Design and Evaluation Methodologies
Community Engagement
E-research with Communities
E-government and E-governance
Participation
Smart Community Services
Sustainability
Universal Usability and Accessibility
Urban Informatics
Tangible Interfaces for Community Interaction
Technologies of Scale Making
Visualisation Techniques
Working across Cultures

http://ct2011.urbaninformatics.net/

#ct2011

http://www.ischools.org/iConference11/2011index/

Our paper, Finding Social Roles in Wikipedia,  about the variety of  roles people perform in Wikis received the best paper award (along with 4 others) in a field of 86 papers.   The 2011 iConference accepted 86 papers, and had about 550 attendees.

The paper is authored by: Howard T. Welser at Ohio University, Austin Lin at Cornell University and Microsoft, Dan Cosley, Fedor Dokshin, Gueorgi Kossinets and Geri Gay at  Cornell University, and Marc Smith from Connected Action.

The paper pdf pre-print is available here: http://oak.cats.ohiou.edu/~welser/Welser.Cosley.plus.Wiki.Roles.pdf

The link to the ACM abstract and pdf: http://portal.acm.org/citation.cfm?id=1940778&CFID=9933318&CFTOKEN=58981138

Abstract: This paper investigates some of the social roles people play in the online community of Wikipedia. We start from qualitative comments posted on community oriented pages, wiki project memberships, and user talk pages in order to identify a sample of editors who represent four key roles: substantive experts, technical editors, vandal fighters, and social networkers. Patterns in edit histories and egocentric network visualizations suggest potential “structural signatures” that could be used as quantitative indicators of role adoption. Using simple metrics based on edit histories we compare two samples of Wikipedians: a collection of long term dedicated editors, and a cohort of editors from a one month window of new arrivals. According to these metrics, we find that the proportions of editor types in the new cohort are similar those observed in the sample of dedicated contributors. The number of new editors playing helpful roles in a single month’s cohort nearly equal the number found in the dedicated sample. This suggests that informal socialization has the potential provide sufficient role related labor despite growth and change in Wikipedia. These results are preliminary, and we describe several ways that the method can be improved, including the expansion and refinement of role signatures and identification of other important social roles.

I will be speaking at the next Predictive Analytics World in San Francisco– March 14-15, 2011 about measuring and mapping social media networks with NodeXL:

Social Data: Advanced Methods – Social (Media) Network Analysis with NodeXL
www.predictiveanalyticsworld.com/sanfrancisco/2011/agenda.php#day2-13a

Networks are the common data structure that unify the otherwise diverse range of social media services. In this session learn how to extract social networks from various social media systems and analyze and visualize the structures found in collections of connections. Learn to use the free and open NodeXL add-in for Excel 2007/2010 to analyze email, twitter, facebook, youtube, www, flickr, and wiki networks.

Here is an example – a map of the connections among the people who recently tweeted the string “#pawcon”.

Connections among the Twitter users who recently mentioned PAWCON when queried on March 14, 2011 including tweets from the period 3/10/2011 15:13 to 3/15/2011 3:51, scaled by numbers of followers.
NodeXL is available from www.codeplex.com/nodexl

The top most between contributors were: @tapan_patel, @jamet123, @zementis, @pawcon, @ibmspss, @sasanalytics, @kristinevick, @waynettetubbs, @dataspora, @inside_r

A recent paper “EventGraphs: Charting Collections of Conference Connections” by Marc Smith from Connected Action, Professor Derek Hansen (College of Information Studies) and Professor Ben Shneiderman (Computer Science/Human Computer Interaction Lab) both from the University of Maryland and has been accepted for publication at the 2011 Hawaii International Conference on System Sciences (HICSS) Conference.  This is the 44th year for the conference. Derek Hansen presented the paper on January 7, 2011.

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

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

Our paper is about visualizing social media and it describes the visualization of the patterns of connections formed when people tweet about events like conferences and news stories.

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.

A collection of EventGraphs are available in flickr: http://www.flickr.com/photos/marc_smith/sets/72157625618025980/

The EventGraph for HICSS this year is here: 20110109-NodeXL-Twitter-HICSS

The top most between contributors to the HICSS Twitter graph this year are: @arcticpenguin @avantgame @barrywellman @clifflampe @dalprof @chandlerism @shakmatt @marc_smith @shen045 and @thecatandthekey

Here is the data set: 20110109-NodeXL-Twitter-HICSS
Graph Metric Value
Graph Type Directed
Vertices 92
Unique Edges 243
Edges With Duplicates 71
Total Edges 314
Self-Loops 0
Connected Components 21
Single-Vertex Connected Components 18
Maximum Vertices in a Connected Component 69
Maximum Edges in a Connected Component 307
Maximum Geodesic Distance (Diameter) 8
Average Geodesic Distance 3.081693
Graph Density 0.032967033

NodeXL Version 1.0.1.159

An article about social media visualization Social Seen: Analyzing and Visualizing Data from Social Networks by Hunter Whitney, appeared in UX Magazine on December 15, 2010.  It provides a great round up of tools and approaches to mapping populations in social media spaces.

Previous HICSS papers:

Gleave, Eric, Howard T. Welser, Marc Smith, and Thomas Lento.  2009.  “A conceptual and operational definition of social role in online community.”   In Proceedings of the 42nd  Hawaii International Conference on Systems Sciences (HICSS), January 5-8. Computer Society Press.  (Best Paper, Digital Media and Communication Mini-Track)

2009 – HICSS – 42 – Best Paper – A Conceptual and Operational Definition of ‘Social Role’ in Online Community

Fisher, D., Smith, M., and Welser, H. You Are Who You Talk To, Proceedings of HICSS, January 2006. (Best Paper, Digital Media and Communication Program)

http://www.connectedaction.net/wp-content/uploads/2009/08/2006-HICSS-You-Are-Who-You-Talk-To-Detecting-Roles-in-Usenet-Newsgroups.pdf

Viégas, Fernanda B., Marc Smith. “Newsgroup Crowds and AuthorLines: Visualizing the Activity of Individuals in Conversational Cyberspaces“, Proceedings of Hawaii International Conference on Software and Systems (HICSS) 2004. (Best Paper: Persistent Conversation Minitrack)

http://www.connectedaction.net/wp-content/uploads/2009/08/2004-HICSS-Viegas-and-Smith-Newsgroup-Crowds-and-Author-Lines.pdf

Here are some sample event graphs:

On November 8th, 2010 I spoke in Seoul, Korea at the 3rd International Conference on Digital Culture on the topic of “Smart Society and Civic Culture“.

Several of my colleagues also spoke at the event, including Leslie Tkach-Kawasaki from the University of Tsukuba, Japan, Han Woo Park from YeoungNam University, Korea, George Barnett from the University of California, Davis and Robert Ackland from The Australian National University, AU.

Robert Ackland from The Australian National University, AU

George Barnett from the University of California, Davis

Han Woo Park from YeoungNam University, Korea

Leslie Tkach-Kawasaki from the University of Tsukuba, Japan

Marc Smith, Connected Action Consulting Group

Han Woo Park‘s research team from YeoungNam University, Korea