2010 - Sept - UC Davis CTSA SNA Community Engagement

CTSA Community Engagement and Social Network Analysis Workshop
September 22-24, 2010
University of California Davis
Clinical and Translational Science Center
Sacramento, California

OBJECTIVES

• Understand the basic concepts, tools, and techniques of Social Network Analysis (SNA) and how they relate to the evaluation of CTSAs and their impact on community research networks.
• Have sufficient exposure to a basic software tool for inputting and analyzing network data in order to undertake a simple social network analysis.
• Enumerate some possible uses of SNA and how to develop data collection tools or use existing sources to study the process and impact of CTSA on community engaged research.
• List primary authors of SNA analyses relevant to CTSA and community engaged research.

Presentation by Noshir Contractor from Northwestern University

10:30-Noon Demonstration of NodeXL Software

Marc Smith.

NodeXL is a free and open add-in for Excel that supports network overview, discovery and exploration. A contributor to NodeXL will provide basic instruction in its use, how to generate useful network statistics and metrics, how to create visualizations of network graphs and how to filter and display attributes that can be used to highlight important structures in networks.

1:00-1:45 Using NodeXL

Joe Hunt, MPH, Indiana University (with Marc Smith)

Using NodeXL to visualize interactions between investigators and CTSA key functions.

I will present a workshop on social media network analysis at the next Network Singularity event at Fort Mason on the Bay in San Francisco on April 30, 2010.

Bay Area and Silicon Valley Network: Special Action/Research Event

Social Media Network Analysis: Next Practices in Social Network Analysis, Tools and Media

Friday 30 April 2010
8:00am -5:00pm
http://www.regonline.com/BAN10
Workshop Abstract
Why do some social media and online groups succeed when others fail? How do different collections of online media and populations of authors and users differ from one another? How do patterns of contribution vary? How do these differences illustrate the roles people play within their communities?

Patterns of contribution and connection determines social media success. Visualizing these network patterns aids implementation, adoption, security and effectiveness of social media. A range of Internet social media including discussion groups, Twitter, enterprise social media, communities-of-practice, blogs and email are presented, analyzed and visualized. Network patterns are explored to illustrate the scope of variation among social media repositories and between types of contributors.

Maps and patterns of interaction deliver a far more comprehensive view of social media. These views generate actionable findings to improve social media effectiveness, syndication and collaborative outcomes. Network analysis and intelligence can guide community cultivation, coordination and development tasks. New network capabilities provision features that improve search, ranking and consumption of user generated content.

A freely available, open source tool will be demonstrated to perform basic social media network analysis for contemporary social media that should be relevant to business models and organizations of all types. Delegates will be equipped to use social network techniques to improve overall effectiveness and impact of social media, communities-of-practice and social software applications. Participants may expect to achieve immediate improvements in key business activities such as marketing, sales, engineering, support, service, innovation and overall organizational effectiveness.

Directions

Registration: http://smanalysistwitter.eventbrite.com/

For example, this is a map of the population of people who recently mentioned “NodeXL” in Twitter.

I see a large cluster of French speaking people who recently picked up on a tweet:

seekoeur: [Blog] Identifier des communautés et cartographier des relations sur Twitter avec NodeXL http://www.seekoeur.com/?p=854

This is a very distinct group from the second cluster around my own account and the recently created NodeXL twitter account.

In contrast, this is the map of all the people who mentioned the keyword “SharePoint” recently in Twitter.

This is clearly a much larger population and one with a dense core of highly connected individuals.  A number of peripheral groups surround the core.  Drilling in can reveal who the center of the center of the network is, a potentially highly influential person.

On October 29th, I will be offering a workshop in Mountain View, California on the application of social network analysis to the measurement of social media.

The workshop will run from 9m to 4pm and include hands-on exercises using real world social media data sets and the free and open NodeXL social network analysis add-in for Excel 2007.  We will create social network metrics and visualizations from personal email, twitter, facebook, and message board records to reveal the broad outline of a community, its various kinds of leaders and active participants, major cliques and clusters, and pivotal events.

The workshop will make use of the NodeXL tutorial:
http://casci.umd.edu/NodeXL_Teaching

Registration at:
http://www.eventbrite.com/event/386418789

I will post the slides for those who cannot attend, but the live event will allow me to help those interested in learning how to visualize social media networks and generate and interpret social network metrics.  What’s an “eigenvector centrality”?  Come find out why that number highlights special people in a network and how to calculate it on your own network data sets.  Find experts, identify the people who are most heavily connected, and key contributors. If you plan to attend, it would be great if you bring sample data: any edge list or matrix is fine.  We can plot and measure sample data participants bring along with them.

I will demonstrate how to create twitter network maps like the one above which shows networks of follows connections among a group of people who tweeted the string “#CHI2010″ (as returned by search.twitter.com).  You can make your own twitter maps with NodeXL!  Similar maps can be made with a user name. In the workshop we will be sure to make a twitter network for anyone there who tweets.

Upon completion of this workshop, participants will:
* be able to understand the basics of SNA, its terminology and background.
* be able to transform communication data (e.g. Twitter, email, flickr, message boards etc.) into network data.
* understand the different possible presentations of social networks, e.g. in a matrix or a sociogram.
* apply network metrics and visualizations to find clusters and key contributors in real world social media data sets.
* get familiar with the use of standard SNA tools and software in general and the NodeXL social network analysis add-in for Excel in particular.
* be able to derive practical and useful information through SNA analysis that would help design an innovative and successful online community.

Who should attend? People interested in community management, social media monitoring and marketing, knowledge management, collaboration and human resources, legal discovery, organizational behavior and management

Registration.

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Other Maps:
Yahoo | Mapquest | Microsoft

For those in the Bay Area there is an event next week of particular interest to community managers, platform developers, researchers, marketers, and software developers: at the Computer History Museum in Mountain View on June 10th is the 2009 Online Community Unconference.  This year 300-400 online community and social media professionals will attend with 50-60 collaborative sessions devoted to social media and online community topics.  

“The Online Community Unconference is a gathering of online community practitioners – managers, developers, business people, tool providers, investors – to discuss experience and strategies in the development and growth of online communities.”

I attended last year and found it to be a valuable use of time: many practioners in the social media space will attend and some will self-nominate and present on a wide range of topics of relevance.  I plan to be there again this year, hope to see you there!

A pioneer of the field, Randy Farmer was in attendance and spoke about lessons and categories of reputation systems.  Randy has experience in this field, having built what could be the very first graphical virtual world.  Some of his observations from those early days of virtual, online, interaction bear re-reading even in today’s megabit broadband world.  Looking back, it is amazing how much of the virtual world package of features could be constructed from Commodore 64s and dial-up modems and how quickly all the social issues emerged, even at 300 baud.  Randy is working on a book on the subject at http://buildingreputation.com/.

• The Lessons of Lucasfilm’s Habitat.(Morningstar & Farmer 1991)
• Habitat Anecdotes.(Farmer 1988)
• Oracle Layza’s Tales from Fujitsu Habitat.(Farmer 1990)

One of the best quips of the conference was from Bill Schreiner from Folio Investing who noted that in the “old days” you used the phone to get to the Internet and that today we use the internet to get to a phone call.  The technology is indeed disruptive!

Sylvia Marino has been managing the communities at Edmunds.com for more than a decade and had useful (if not flattering) things to say about the state of sentiment analysis.  Her preference is to work with moderators who personally do read nearly all messages and deeply understand the topics of interest and attitudes of the community.

A stand out presentation came from Jen Burton from Digg.com whose talk about the nature of managing a huge community of contributors was insightful and funny.  Her suggestion to treasure the happy moments when they come is sound, as well as the warning to avoid getting sucked into conflicts with a minority of users who have time on their hands.

Nova Spivack presented an overview of Twine and its stages of growth with its community.  Twine as I understand it is a kind of super charged version of a system like del.icio.us that uses natural language processing and a web crawler to build a more useful set of pointers to a web page than is created by a standard entry in del.icio.us.

More photos on flickr.