Table Of Contents

Foreword
Introduction
About the Question
Related Concepts
Choosing Subjects: Where Does Responsibility Matter Now?

Genetics And Healthcare
Thomas Murray, The Hastings Center
Ignacio Chapela: Drawing a Boundary Around the Lab
Arthur Caplan: Innovation as Politics
David Magnus & Mildred Cho: True Fictions

Nanotechnology
Christine Peterson: Nanotechnology and Enhancement
Lawrence Gasman: Nanomarkets

Robotics And Computing
Ronald Arkin: Embedding Values in Machines
Jeff Jonas: Applying the UN declaration of human rights
Marc Smith: Invention, mitigation, accounting and externalities
Mikko Ahonen: Open Innovation … and Radiation Safety

Design
Roberto Verganti: Varieties of Design Innovation
Michael Twidale: IRBs, Design, Empowerment,
Accountability, Sustainability

My comments from the volume are after the fold…

Marc Smith: Invention, Mitigation, Accounting and externalities

If responsibility is about effects, then systems of measurement and observation are key to any understanding of responsible innovation.

Dr. Marc Smith (http://www.connectedaction.net) is formerly a Senior Research Sociologist leading the Community Technologies Group at Microsoft Research in Redmond, Washington. His group focused on computer-mediated collective action, and studied and designed enhancements for social cyberspaces.  Smith now leads the Connected Action Consulting Group in Silicon Valley. In particular, he is interested in the emergence of social organizations like communities in online conversation and annotation environments. The goal is to identify the resources groups need in order to cooperate productively.

Smith is the co-editor of Communities in Cyberspace, which explores identity, social order and control, community structures, dynamics, and collective action in cyberspace, and has developed software called Netscan that measures and maps social spaces in the Internet, starting with the Usenet. A related effort, Project AURA, allows users to associate conversations (and more) with physical objects using mobile wireless devices and web services.

Responsibility in innovation often comes after the fact. “The history of the technology is seize new power—then mitigate, mitigate, mitigate all the pathologies,” Smith says. “How long was it from the Model T Ford to safety belts?”

Responsibility can be improved through measurement of effects. “May I suggest that your best method for mitigation is documentation of negative externalities?” Smith says. “You can ‘govern’ innovation when the language and the data to document negative consequences are more available, freely available, easily used. Then you have a technology regulation and negative externality problem, and that I think is one that is more tractable.”

Part of that is stakeholder identification. Smith argues that it is easy to identify stakeholders, at least after the fact, because, “They’re at the top of the legal documents that are served to you. That’s how you identify the stakeholders, the ones that actually get the job done, make themselves known, tell you that you’re creating negative externalities for them, and insist that you [provide] remedy.”

But it’s also important to recognize the initial position of most innovators. “Innovation typically comes from the people who are most squeezed out of the sweet solution space,” Smith says. “You don’t innovate unless you have to… Innovation is the behavior, I think, of marginal actors in an ecological landscape.”

The deck illustrates the use of NodeXL to extract several social media networks from systems like twitter and facebook to generate maps of communities and identify people and objects in key locations.

We  discussed ways to leverage social networks  networks beyond personal connections – to provide business value.  We talked about ways to efficiently and effectively use social media to market and grow your business.

Using social media to grow and market your business

I spoke about tools, like NodeXL, that we have been building that create maps of the relationships among a population of people gathered by some shared attribute, like mentioning a keyword or hashtag.

Here are a few excerpts from the event created by Tendo Communications:

The Second Conference on Online Deliberation: Design, Research, and Practice (OD2005/DIAC-2005) was held at Stanford University May 20-22, 2005. From that event there is now a book,  Online Deliberation: Design, Research, and Practice, edited by Todd Davies and Seeta Peña Gangadharan (CSLI Publications, November 2009).  All content in the book is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License.

I will call out a few of the many interesting chapters, one of which I contributed to:

Chapter 5: Friends, Foes, and Fringe: Norms and Structure in Political Discussion Networks (John Kelly, Danyel Fisher, and Marc Smith, pp. 83-93)

And two from colleagues who report on tools for facilitating political debate and decision making:

Chapter 6: Searching the Net for Differences of Opinion (Warren Sack, John Kelly, and Michael Dale, pp. 95-104)

Chapter 26: Online Civic Deliberation with E-Liberate (Douglas Schuler, pp. 293-302)

The book is a great guide to the many ways computer-mediated interaction technologies are being used to build consensus or tear it apart!

—

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.

After visiting the Oxford Internet Institute on December 4th, I will be visiting Aachen University to talk about social media network analysis this December 7th and 8th.

I will be visiting with my hosts, Zinayida Petrushyna and Ralf Klamma who have been doing insightful work exploring social media sites like Media Wikis and Wikipedia.  The Wiki Watcher project is a big favorite of mine.  Their working group on Social Network Analysis on Dynamic Digital Networks is of particular interest.

While I am back in Aachen, I hope I will get to see some of the folks I met at the “European Microsoft Innovation Center” (EMIC) located there.  They focus on research into embedded systems which I see as having vast implications for the ways computers sense social relationships.  When sociologically aware machines are widely used, we will have new ways of building and maintaining relationships.

I will give three presentations over two days in Aachen – I hope you can attend if you are in the area!

Monday, December 7, 2009 (in cooperation with the Web Science II course at RWTH Aachen University):

12:15 – 13:45 Social Media Visualization Analysis: overview of work to visualize social media using treemaps, histograms, scatterplots and social network diagrams

Using social media makes evidence of social relationships into machine readable data streams.  The resulting data sets contain time series, hierarchy, and network data structures that can be visualized to illustrate the range of variation in social media data spaces and participants.  Histograms, line charts, treemaps, and network diagrams can be used in concert to illuminate the many facets of behavior and population present in social media spaces.  Resulting images illustrate the range of variation of individual and collective formations in social media spaces.

16:00 – 17:30 NodeXL – A hands-on guide: a workshop style review of sample data sets that are processed through NodeXL operations to generate metrics and a visualization that tells a story.

As social media networks proliferate there is a growing need for tools to manage, analyze, and visualize network graphs.  NodeXL is an add-in for Office 2007 that provides social network diagram and analysis tools in the context of a spreadsheet application. Adding the directed graph chart type to Excel opens up many possibilities for easily manipulating networks and controlling their display properties. In this workshop the steps needed to install and productively operate NodeXL for Office 2007 are reviewed. The free and open NodeXL add-in provides directed graph charting features within Excel, allowing users to create node-link diagrams with control over each node and edge color, size, transparency and shape without requiring the use of a command line interface or programming language. Since NodeXL builds within Excel, all of the controls and programmatic features of Office are available. Additional features of NodeXL generate social networks from social media data sources like personal e-mail (drawing data from the Windows Desktop Search engine) and the Twitter social network micro-blogging system. Arbitrary edge lists (anything that can be pasted into Excel) can be visualized and analyzed in NodeXL. This session will provide a walk through the basic operation of NodeXL.

Tuesday, December 8, 2009

10:00 – 11:00 In the future my phone will notice your phone: from ephemeral to archival societies

New sources of data from everyday life are being captured and recorded with mobile devices, creating a new stream of archival material that is richer than all but the most obsessively observed biographies. Many organizations are adopting social media and creating data sets that map their internal social network structure as an accidental by-product.  Studying these data is sets is a focus of growing interest. Research projects like SenseCam are now becoming products and services like nTag, Spotme, Fire Eagle, and Google Lattitude using devices like iPhone and G1 are weaving location into every application.   When my phone notices your phone a new set of mobile social software applications become possible that capture data about other people as they beacon their identifies to one another. Additional sensors will collect medical data to improve our health and safety, as early adopters in the “Quantified Self” movement make clear.  Social media systems are being linked to one another to enable cascades of events from a single message as status updates are passed among Facebook, LinkedIn, Twitter, and blogs automatically aggregate the results of searches and post articles that themselves may trigger other events.  Taking a photo or updating a status message can now set off a series of unpredictable events.  The result will be lives that are more publicly displayed than ever before.  Add potential improvements in audio and facial recognition and a new world of continuous observation and publication emerges.  Some benefits, like those displayed by the Google Flu tracking system, illustrate the potential for insight from aggregated sensor data.  Risks include more efficient state and corporate surveillance and self-imposed censorship.

On December 4th, I will be attending the Oxford Internet Institute‘s Forum on Relationships and the Internet which will feature researchers focused on computer-mediated relationships.  Rather than being used primarily to access information, people often use networked computing to access people, creating or sustaining relationships with others.  There are many ways in which the Internet and a range of applications are now used to find new people, find old people, maintain primary connections, sustain weak ties, and build personal and professional relationships.  Dating sites are a clear part of the Internet relationship picture but so are professional “dating” services like LinkedIn or professional services directories like Craig’s List, social networking services like Facebook, and “normal” tools like email.  People now use a concerted set of Internet tools in building and maintaining their relationships.

Researchers are interested in online dating and social networking.  They are now exploring the role of information and communication technologies in all forms of interpersonal relationships.  Practitioners from a growing and international relationship industry who want to cultivate and manage these relationship systems will attend along with policy-makers who seek to regulate their uses towards positive ends and avoid abuses.

Speakers include:

• Bill Dutton, Oxford Internet Institute
• Nai Li, Oxford Internet Institute
• Bernie Hogan, Oxford Internet Institute
• Ellen Helsper, London School of Economics
• Monica Whitty, Nottingham-Trent University
• Barry Wellman, University of Toronto and Director of NetLab
• Joe Walther, Michigan State University
• Nicole Ellison, Michigan State University

Research in Internet relationships goes beyond a focus on dating sites and services to incorporate all the stages and types of relationships being shaped by social information technology.  My demonstration will illustrate the ways NodeXL can map relationships in a variety of social media spaces, including YouTube, flickr, email, twitter, and (with the help of Bernie Hogan’s ego-network importer) Facebook.  These maps can be a useful ways of distinguishing different kinds of relationship patterns present in these spaces, identifying key participants who acts as hubs or bridges.

The OII also maintains a video webcast site with a great collection of recordings of lectures and panel discussions of a variety of  topics related to the Internet and society.  In particular, check out Duncan Watts presenting a talk on “Using the Web to do Social Science“.

http://books.google.com/books?id=v4A39158MUQC

At the core of her extensive, empirical, research into the ways humans share common goods and resources is a set of eight core design principles.  These “8″ principles for successful creation and consumption of a resource are documented in the book “Governing the Commons”

Next week I will be attending and discussing mobile social media and social networks at the Mobile Web Africa conference in Johannesburg, South Africa. It is my first time to Africa and I am excited to both visit and to discuss how mobile networked devices can change social organizations.  Mobile devices are in many ways more important in emerging and developing regions where the availability of these tools enable the first voice and data services that have ever been affordable and reliable, let alone mobile.  There are vast opportunities in this space, a topic well reviewed in the recent issue of the Economist:

The Mobile Web Africa event will focus on these key questions:

1. How will the industry evolve to a point where the vast majority of people have access to the mobile web and the content they want to view?
2. How will the industry fully exploit existing and future opportunities?
3. How can PC or mobile based developers and start-ups monetise their innovation and creativity to grow in to companies that will drive the expansion of the ecosystem?
4. How can Operators, Original Equipment Manufacturers, global associations and other mobile powerhouses assist their smaller partners?
5. How can societal and economic problems be tackled by the development of the capabilities of the mobile device?
6. What handsets, standards, networks and designs will allow consumers to successfully access the content and consume it?
7. How will the consumer be able to discover that content – through an Application, Browser, Search Engine, Advert, Social Network?

I will focus my discussion on the idea of the “Electrification of the Interaction Order” and topics related to the growing use of sensors on mobile devices and the sharing of the resulting data.  A service like SenseNetworks is a  good example of a mobile data collection, analysis, and presentation service.  Other sites, like Quantified Self, CureTogether, and FitBit, are examples of the social movements, web applications, and devices that are emerging in the self-monitoring medical tracking space.  These communities overlap with the trail based exercise communities of runners, bikers, skaters, hikers, and skiers, some with artistic inclinations.  I see a new wave of devices that are extensively quantify your “self” and “others”, perhaps when people swap sensor data with one another.  The recent work of Nathan Eagle and his co-authors illustrate the possibilities of using many devices with (already existing and widely used) sensors can generate remarkable maps of human behavior.  Much of this data will take the form of social networks as people are linked by “hyperties” – forms of association and connection that are authored by machines from the records of association and behavior.  People will be linked who have never met, in the same way that web book store customers who have never met can be linked by common browse and purchase patterns.  Hyperties will be formed by shared use of location, even if at different times, or patterns created by passing through different spaces at different times but in common patterns (Starbucks, then gas?  Or subway then tea shop?).  The notion of “Tribes” used by the SenseNetworks company is a good example of this approach.    The Economist is all over this topic, with another article “Mobile phones Sensors and sensitivity” that captures the topic.  Jonathan Donner’s work is also a good resource for insights on the role of mobile technology in many parts of the world.  The ability to enable a form of banking service is a particular benefit for the many people who do not have access to banking services.

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.

View Larger Map

Other Maps:
Yahoo | Mapquest | Microsoft

This weekend is the Social Computing 2009 conference in Vancouver, B.C.  It is a gathering of many people doing research on social media useage.  Many papers are about tagging systems, blogs, wikis, message boards, and social networking services.

Along with several co-authors, I contributed to three papers in this year’s conference:

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

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.

Abstract: Broadening adoption of social media applications within the enterprise offers a new and valuable data source for insight into the social structure of organizations. Social media applications generate networks when employees use features to create “friends” or “contact” networks, reply to messages from other users, edit the same documents as others, or mention the same or similar topics. The resulting networks can be analyzed to reveal basic insights into an organization’s structure and dynamics. The creation and analysis of sample social media network datasets is described to illustrate types of enterprise networks and considerations for their analysis.

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.

The 2009 American Sociological Association Annual Meeting was held in San Francisco, California, August 8-11.

The ASA attracts thousands of sociologists, a subsection of whom have  a passion for the study of the Internet and its many forms of social impacts and uses.  The Communications and Information Technology Section of the American Sociological Association (CITASA) is the group that gathers many forms of social science research on the creation and uses of information technology.  This year’s meeting included two CITASA panels, round tables, a business meeting with awards, and a (windy!) boat ride through San Francisco Bay and beneath the Golden Gate Bridge.

The CITASA sponsored papers at the conference are listed below.  The range of work illustrates the continued interest in social science studies of the impacts of information technology.

Session 1: Cultural Divergences and Convergences: Mediated Communication, Community, and Social Networks
Presider: Laura Robinson, Santa Clara University
10:30 – 12:10 PM, Location: Parc 55 Hotel

Reframing Public Space Through Digital Mobilization: The Case of Flash Mobs
Virág Molnár

The Consumption of Online News at Work
Pablo J. Boczkowski

French Software Politics: The Freedom Discourse and Globalization from Below
Sara Schoonmaker

Convergence in E-Campaigning: Comparing the Use of Attacks on German and American Political Web Sites
Eva Johanna Schweitzer

The Flow of Mediated Culture: Trends of Supply and Demand 1960-2005
W. Russell Neuman

Session 2: Sociology of Communications and IT
Presider: Keith N. Hampton, University of Pennsylvania
2:30 – 4:10 PM, Location: Parc 55 Hotel

Gauging the Impact of e-Research in the Social Sciences
Ralph Schroeder, Eric T. Meyer, University of Oxford

Does Previous Technology Use Influence Later Opinions Linking Use to Work Experiences, Relationships, and Time?
Noelle A. Chesley, University of Wisconsin-Milwaukee

Medical Conversations in Technology Enabled Communities: Perceived Benefits of Participation in Online Patient Communities
Gul Seckin

Model Failure: Assemblages, Performances, and Uneasy Collaborations in Commercial Construction
Gina Neff, University of Washington; Brittany Fiore-Silfvast, University of Washington; Carrie Sturts Dossick, University of Washington

Core Discussion Networks, Internet and Mobile Phone Use: New Media are not Increasing Privatism in America
Keith N. Hampton, University of Pennsylvania; Lauren Sessions, University of Pennsylvania; Eun Ja Her, University of Pennsylvania

————–

Round tables (1-hour): Open Submission
Organizer: Steven G. Hoffman, SUNY Buffalo
8:30 – 9:30 AM, Location: Parc 55 Hotel

Table 1: Communication and Information Technologies at the Producer-Consumer Nexus
Presider: Chris Rhomberg, Fordham University

A Tale of Two Newspaper Chains: Gannett, Knight Ridder, and the Crisis of American Newspapers
Chris Rhomberg, Fordham University

Analyzing design activity in architect and user talk-in-interaction: a preliminary analysis
Rachael Luck, University of Reading

Distributed Cognition and the Emerging Peer-to-Peer Production Model
Michael Restivo, Stony Brook University

Table 2: Communication and Information Technologies, Community, and Sexuality

Negotiating identities/remediating queering desires: Coming out and coming of age online
Mary L. Gray, Indiana University

Sociological Examination of People’s Attitude Towards Online Dating
Xue Liu, Clemson University

The Amorous Migrant: Race, Interracial Desire and Relocation in Cyberspace
Nicholas Andrew Boston, Cambridge University/Lehman College of the City University of New York

Virtually Gay: The Internet and the Construction of Hybrid Queer Identities and Transnational Gay Cultures

James Paul Thing, University of Southern California

Table 3: The Internet and Political Engagement I
Presider: Phil Howard, University of Washington

Bringing the body back in: considering the role of the body in deliberative democracy
Amy Stuart, New School for Social Research ICANN and Internet Governance
Hangwoo Lee, Chungbuk National University

Social Capital and Political Mobilization in Online Community
Jun Young Ah, Yonsei university; Jeong-han Kang, Yonsei University

Vitalizing Donation Culture in Korea: Comparison of Strategies between Traditional Off-line and New Online Donations
Sun Hyoung Lee, Yonsei University

Table 4: The Internet and Political Engagement II

A Facilitator of Civic Engagement in Online Group Contexts
Ja Hyouk Koo, University of Virginia

Muslim resistance online: a diasporic Pakistani punk music subculture on the Internet
Dhiraj Murthy, Bowdoin College

Transylvania, the Internet, and the Strategic Construction of Ethnic/National Identity
J. Patrick Williams, Nanyang Technological University

Table 5: New Technologies, Social Change and Knowledge
Presider: James A. Evans, University of Chicago

How the Internet Shrinks Knowledge By Extending It
James A. Evans, University of Chicago

Socializing the Mobile Phone: Young Urban Poor’s Fascination at Play
Lip Soon Wong, Telenor Research and Innovation Center

Social Networks inside the Enterprise: analyzing colleague link patterns in an IT workplace
Marc Smith

Table 6: Computer Mediated Communication, Social Capital, and Symbolic Interaction
Presider: Simon Gottschalk, University of Nevada- Las Vegas

Dramaturgy, Technology and Public Health: Finding Sex Partners Online among Men who have Sex with Men
Anthony P. Lombardo, University of Toronto

eIntelligence: Social Intelligence in Computer-Mediated Communication
Simon Gottschalk, University of Nevada- Las Vegas

How to Ground a Child in Cyberspace: Parents’ Exploration of Norms and Rules
Mito Akiyoshi, Senshu University

Structured Talk and Web 2.0: Blogs and Community Formation

Kenneth M. Kambara, California Lutheran University

Table 7: Communication Technologies and Network Formation
Presider: John P. Robinson, University of Maryland

Events and Attendees in Two Countries: Factors Influencing the Size and Composition of Online Social Groups
Ryan M. Acton, University of California, Irvine

From each according to media? Testing Wellman’s theory of networked individualism
Bernard Hogan, University of Toronto

The Composition of a Korean Immigrant Social Network
Sun Kyong Lee, Rutgers University

Table 8: Information Production, Coordination and Distribution

Order, Coordination and Uncertainty in Online Information Systems”
Judd Antin, University of California, Berkeley
Coye V. Cheshire, University of California, Berkeley

When High Commitment Hurts: Evidence from Wikipedia
Andreea Gorbatai, Harvard University

Wikipedia: Community or a social movement?
Piotr Konieczny, University of Pittsburgh

Dr. Karen Cook, Stanford University

Dr. Toshio Yamagishi, Hokkaido University

Dr. Jodi O’Brien, Seattle University

and myself.

Earlier in the year, in March 2009, many people gathered at De Neve Plaza at UCLA to remember Peter Kollock.

On Monday, September 14th, at 10:30 PST, I met on the phone with Jerry Michalski and other participants for one of his regular weekly Yi-tan conference calls to discuss the scholarship and personal legacy of Peter Kollock.  In this podcast, I spoke about my years of working with Peter to apply the models of collective action dilemmas, common pool resources, cooperation, and conflict to the creation of Internet social institutions and resources. I discussed Peter’s work with his colleague Jodi O’Brien, and the lasting impact of his research into studies of cooperation, collective action, and common goods as well as his impact on students, business, and the field of social science.  Jodi and Peter were colleagues and co-authors for many years, creating a widely used text The Production of Reality: Essays and Readings in Social Psychology as well as several other publications.  I worked with Peter while studying for my Ph.D. at UCLA in Sociology.  Peter and I wrote about the sociology of the Internet together and co-edited a book Communities in Cyberspace.

I will post a few links to some of Peter’s work that has had the most impact on me in upcoming posts.

Listen here!

On August 5th and 6th I led a workshop with Martha Russell on social network analysis of social media as part of the Stanford Media X Summer Institute on New Metrics for New Media: Analytics for Social Media and Virtual Worlds this Summer.

New Metrics for New Media:  Analytics for Social Media and Virtual Worlds
Organizers:  Martha Russell, Marc Smith
August 5-6

Social media and virtual worlds offer two important frontiers for measuring earned engagement. In both, audiences are actively engaged as participants. This workshop covered foundational concepts in media measurement, describe new frontiers in measuring audience engagement in social media and virtual worlds, and provided hands-on experience in using new analytical tools.

This session also provided a walk through the basic operation of NodeXL, including generation of social networks from social media data sources like personal e-mail (drawing data from the Windows Desktop Search engine) and the Twitter social network micro-blogging system. Arbitrary edge lists (anything that can be pasted into Excel) can be visualized and analyzed in NodeXL. Attendees were encouraged to bring an edge list of interest. Sample data sets were provided.

Video about the New Media for New Metrics Workshop

Agenda WEDNESDAY, August 5: #124 Wallenberg Hall

08.30 – 09.00 – Welcome, Introductions & Overview

Martha Russell, Director, Media-X, Stanford University
Marc Smith, Internet Sociologist, Connected Action Consulting

Martha spoke about the changing media landscape and the need to measure new media in the mix of media consumption measurements.  She suggests that old measures may not always fit new media and that new media offer new opportunities (and challenges) for measurement.  Martha runs the Media-X program at Stanford that ran the workshop.

09.00 – 10.00 – The MEdia Generation (and others): Trends in Media Multitasking in the US and China

Don E. Schultz, Northwestern University Agora-IMC, Inc, BigResearch

Professor Schultz teaches marketing and communication at Northwestern University.  He runs a series of surveys about media consumption in the US and in China.  The results show people consuming multiple media at the same time, but not in the same mix (China uses mobile more than desktop).

10.30 – 11:30 – Panel: Metrics for Management Decisions

Moderator: Martha Russell, Media X at Stanford University

Richard Rommel, Senior VP Emerging Business, Best Buy
Blaine Baggett, Executive Manager, Office of Communication and Education
Jet Propulsion Laboratory, NASA
Louis-David Mangin, GrinShot
Maury Giles, Founder, Pursuit

Richard Rommel (Best Buy) discussed their Twitter strategy and commercials.  Best Buy now features their employees as a service via twitter to all askers and features that in their TV commercials.

JPL in Pasadena is using the web to push the “science is cool” (and fundable) message to all who will listen.  When NASA lands something on Mars its the JPL that gets the huge traffic spike.  They are opening up conversations between researchers and the public and increasing the surface area for science media.

11:30 – 12:00 – Synergies Between Search and Social Metrics

David A. Shamma, Yahoo Research

Ayman spoke about measuring engagement in a Yahoo Messenger video sharing and chat feature.  He found that chat activity spikes during the credits.  Except in Japan where strings of “wwwwwwwwwwwww” denote laughter and continue through out a shared video session.

Ayman also did a study of Twitter usage during last year’s political debates.  He found the chat did not echo the terms used in the debate.  Chat activity also spiked after the debate.

13:00 – 14:00 – Measuring Social Media & Digital WOM

Michael Wu, Chief Scientist, Lithium

Michael presented the ingredients of the Lithium Community Health Index which (pictured) includes the notion of interactivity (speed to reply).

14:00 – 15:00 – Panel: Metrics for Moderating and Managing Communities

Moderator: Marc Smith, Internet Sociologist, Connected Action Consulting

Sameer Patel, Pretzel Logic
Gail Ann Williams, Director of Communities, Salon.com

Gail and Sameer focused on the ways they directly manage communities in a commercial environment.  Gail tuns the community for Salon’s Table Top and Well social spaces.  She runs fee based spaces that require customer retention (but sometimes wish they could selectively apply customer ejection!).

Sameer consults on the selection and use of enterprise social media.  He focused on the metrics his customers want to see in an internal deployment, focused on usage and connection rates among users.

15:15 – 17:00 – Social Network Analysis Tutorial: Part 1
Concepts, Data, & Tools for Producing the Social Graph

Marc Smith, Internet Sociologist, Connected Action Consulting

I showed the slides previously presented at the Catalyst Conference, this time in a longer form at the workshop: http://www.slideshare.net/Marc_A_Smith/2009-catalyst-conference-social-media-research slides focuse on the use of social network and activity analysis to identify key contributors in social media spaces.

17.00 – 17.30 – Discussion: Navigating the Terms in Social Media Metrics

Moderator: Don Schultz

———————————————–
Agenda THURSDAY, August 6: #124 Wallenberg Hall

08.30 – 09.30 – Patterns of Mobile Media Advertising–Taking 3G Portals as an Example

Chunlin Duan, South China University of Technology Profit

Professor Duan is Dean of the School of Communication at South China University of Technology.  She described mobile device usage in China (huge!) and the major focus on IM, chat, and message boards, along with the dominance of QQ and its virtual goods and currency.

09.00 – 09:30 – Cell Phone Usage in Japan for Social Networking and Advertising

Neil Rubens, University of Electro-Communications, Tokyo

When toddlers have cell phones mobile device penetration is high!  Japan is highly mobile (although on its own island of technology) and using social network services via their devices.

09:30 – 10.30 – Panel: Emerging Metrics for Virtual Worlds & Immersive Environments

Moderator: Greg Nuyens, Qwaq Forums
Gene Yoon, Former CFO, Second Life
Parvati Dev, Innovations in Learning
Henrik Bennetsen, Stanford Humanities Lab

Gene Yoon is the former CFO of Second Life, he spoke about the use of metrics in his business.  He focused on engagement as the behavior he wanted to measure.

Parvarti Dev is a former Stanford Professor using virtual reality social worlds to role play emergency room procedures among nurses and doctors.

11:00 – 12:00 – Trends in Metrics for Self Monitoring

Gary Wolf, Sr. Editor, WIRED

Gary is documenting the emerging world of the “Quantified Self” – people using mobile devices with sensors and networks to collect detailed records of their own behavior and medical vital statistics.  These data sets, in aggregate, may reveal new insights for evidence based medicine, self improvement, and public safety.

13:00 – 15:30 – Social Network Analysis Tutorial: Part 2

Concepts, Data, & Tools for Filtering and Decorating the Social Graph

Marc Smith, Internet Sociologist, Connected Action Consulting

A step-by-step guide to creating, analyzing, and visualizing a social network.

16:00 – 16:30 – Discussion and WrapUp: Gleaning Meaning from Measurements

Moderator: Martha Russell

]]> http://www.connectedaction.net/2009/09/12/recently-stanford-media-x-workshop-new-metrics-for-new-media-analytics-for-social-media-and-virtual-worlds/feed/ 0 http://www.connectedaction.net/2009/09/12/july-catalyst-conference-on-enterprise-social-media-in-san-diego/?utm_source=rss&utm_medium=rss&utm_campaign=july-catalyst-conference-on-enterprise-social-media-in-san-diego http://www.connectedaction.net/2009/09/12/july-catalyst-conference-on-enterprise-social-media-in-san-diego/#comments Sat, 12 Sep 2009 10:45:05 +0000 Marc Smith http://www.connectedaction.net/?p=1011

The Catalyst Conference was July 27-31 in San Diego which gathered many people to discuss new technologies for enterprise computing.
On Wednesday, July 29 at 11:15 a.m. I gave a presentation about the use of social network analysis within the enterprise.

Session Details: Social Network Analysis: A New Source Of Business Intelligence

Mike Gotta, Principal Analyst, Burton Group with Marc Smith, Internet Sociologist

Where do people go when they need subject-matter expertise? How do you discover someone in your company who knows someone in a firm you’re trying to sell products and services into? Who is the person everyone goes to when they need to find out what’s really going on? Such relationships within organizations have been difficult to identify and leverage because they are often invisible to those outside people’s informal and personal networks. Technology has compounded the problem by fragmenting interactions between people across a multitude of tools. The advent of social networking sites within the enterprise (e.g., a “Corporate Facebook”) has triggered a resurgence of interest in the visualization and analysis of relationship structures.  Social network analysis represents a new source of insight that aids a variety of business activities. It can also reveal interaction patterns and relationship structures that help strategists improve organizational effectiveness.  As social networks gain increased adoption, numerous issues arise:

• How should relationship data be leveraged? What are the applications?
• Who conducts this type of work – do IT organizations have the skills?
• Will identifying “social roles” become a key component of organizational development and management practices? What are the privacy concerns?

In this session, Marc Smith will outline SNA trends and discuss real-world examples with Principal Analyst Mike Gotta of Burton Group.

Some tweets from the talk:

• Spesh00: I think Marc Smith just completely validated my prior statement about leveraging my social score against my knowledge tags. #catalyst09
• atownley: Moving discussions for internal use from email to messageboards, etc. to segregate personal/corp data – Marc Smith #smchat #catalyst09
• aewang: Chief Social Scientist (Marc Smith) – what a cool title! #catalyst09
• aewang: Love Marc Smith‘s comment about ascribing status vs. achieving status. achieving hard to do w/o social media #catalyst09
• atownley: Very interesting presentation from Marc Smith of Telligent on social analytics of many different sources for “networks” #smchat #catalyst09
• aewang: Interesting presentation from Marc Smith @Telligent on social analytics #catalyst09
• Spesh00: NodeXL – Free program for Social Analytics.. Looks slick as all get out. #catalyst09
• Spesh00: Social Network Analysis from Mike Gotta and Marc Smith. I wanna be the “Discussion Person”… #catalyst09

There were several notable points made during presentations that captured my attention:

• Social Media platforms are seen as meta identity servers.  Where LDAP and AD are not end user editable (usually), social media allows self-annotation AND annotation on others.
• Metrics in enterprise social media can be applied to assess how much an organization is isolated in silos: compartmentalized enterprises have few links across organizations.
• Issues with employees who leave (and might someday return) – how to keep the information while freezing the identity.
• Identity Management is a major area: lots of talk about “ascribed” roles (you are a person who can approve payments) versus “achieved” roles (you start behaving like an Answer Person).
• Identity leakage and diffusion: what happens when internal profile data gets outside or outside social media gets pulled internally?  If content is created on employee owned device and on personal time is it owned by the corporation?
• Citrix embraces employee provisioned hardware: provides $2,100 to employees to buy a laptop that meets or exceeds corporate requirements.  They own it and take it with them if/when they leave.
• Booz Allen Hamilton embraces internal social media, demonstrates value to organization versus “free and public” sites.  Will onboard 5K NEW EMPLOYEES this year!  Need to integrate new people fast!

The Communities and Technologies conference is holding its 4th meeting in Penn State June 24-27.  This conference gathers a range of scholars interested in online community, social media, social networks, and mobile social software.  A paper “Analyzing (Social Media) Networks with NodeXL” has been accepted for publication in the conference!  Congrats to my co-authors!

Paper Title: Analyzing (Social Media) Networks with NodeXL

Authors: Marc Smith (Telligent Systems), Ben Shneiderman (University of Maryland), Natasa Milic-Frayling (Microsoft Research), Eduarda Mendes Rodrigues (Microsoft Research), Vladimir Barash (Cornell University), Cody Dunne (University of Maryland), Tony Capone (Microsoft Research), Adam Perer (University of Maryland, now at IBM Research), Eric Gleave (University of Washington)

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. ]]> http://www.connectedaction.net/2009/06/08/2009-ct-nodexl-and-social-queries-a-social-media-network-analysis-tool-kit/feed/ 0 http://www.connectedaction.net/2009/06/02/conference-enterprise-20-in-boston-june-22-25/?utm_source=rss&utm_medium=rss&utm_campaign=conference-enterprise-20-in-boston-june-22-25 http://www.connectedaction.net/2009/06/02/conference-enterprise-20-in-boston-june-22-25/#comments Tue, 02 Jun 2009 17:06:49 +0000 Marc Smith http://www.connectedaction.net/?p=1052

The upcoming Enterprise 2.0 conference in Boston June 22-25 features several presentations of possible interest. George Dearing and I will both be on panels and, centrally, there is a presentation from Telligent co-founder Rob Howard about what is new at Telligent Systems:

Enterprise 2.0: Work, Productivity and ROI Today’s ever-changing workforce requires that enterprises tackle an array of shifting demands. Adapting to the various ways people collaborate and work together without actually being in the same place is now an organizational necessity, not just an option. Join us for this informative session as Rob Howard, Founder of Telligent and an innovator of online collaboration strategies, presents Enterprise 2.0 and social computing in the context of work, productivity and ROI. Enterprises that have embraced collaborative computing and analytics are realizing results in increased workforce productivity, expanded input and insight from customers and partners, and now have the ability to manage and report on the value of these efforts. Join us for this session and walk away understanding how you can prepare today for the future of work.

Speaker – Rob Howard, Co-Founder, Telligent

George Dearing from Telligent and I will both be on additional panels at the conference.  I am looking forward to the chance to present along with Kate Niederhoffer from Dachis again; we presented at Web 2.0 on the topic of “Beyond Buzz: On Measuring a Conversation” which I think was well received.  Details below:

In one panel, George will be talking about the role of social media in customer relationship management:

Web 2.0 and Selling #e2conf22
The idea that markets are conversations is common wisdom today. But when a handful of visionaries drafted the Cluetrain Manifesto about 10 years they could not have foreseen the explosion of Web 2.0 tools over the past decade that would bring customers so quickly and directly into all aspects of sales and marketing. Today’s buyers are not content to be passive recipients of controlled and targeted information; they are demanding an equal voice in the sales process, sharing information, engaging with other buyers in digital communities, and doing competitive research online.  That means sales people have to be smarter and learn how to translate the old fundamentals of good selling into “social selling” -a process to build trust, generate interest and eventually close the deal.

Moderator – Robin Carey, CoFounder and CEO, Social Media Today LLC

Speaker – George Dearing, Senior Corporate Evangelist, Telligent
Speaker – Mark Woolen, Vice President, CRM Product Strategy, Oracle
Speaker – Romi Mahajan, Chief Marketing Officer, Ascentium
Speaker – Timothy Jones, CEO, Buzzient

I have the great opportunity to rejoin Kate Niederhoffer for a panel along with  Bruce MacVarish (Avaya) and Daniel Debow (Rypple.com) to discuss the new measurements available when an enterprise adopts a social media platform.

Metrics in the Hands of Users: Empowering the Enterprise 2.0 Workforce #e2conf45
As the enterprise transforms, how do the metrics evolve and who owns them? We readily acknowledge the shifted priority on interactions, but how do we measure them and who does this information benefit most? Today’s enterprise is built on metrics that are relevant to business goals; management closely monitors progress. From hierarchy to flat: supplying the E2.0 workforce with metrics that facilitate relevant behavioral communicating with the right people in the right ways– will play a clear role in managing the change an enterprise will endure as it shifts its tools, processes and culture.

Moderator – Kate Niederhoffer, Senior Partner, Dachis Corporation
Dr. Niederhoffer is part of the founding team at Dachis Corporation. She joined from Nielsen Online where she was the VP of Measurement Science, liaising between Research, Product, and R&D.

Speaker – Bruce MacVarish, Director, Business User Group, Avaya
Speaker – Daniel Debow, CEO, Rypple.com
Speaker – Marc Smith, Chief Social Scientist, Telligent

My colleagues from Microsoft Research will also be presenting:

Technology Innovation – Exploring Beyond Social Computing Tools in the Market Today
We know what social computing tools are available in the market today, but how are researchers thinking about technology innovation? How are organizations using social networking and driving adoption? Microsoft Research has been working on projects that dig into the analytics of how the intelligence gathered can provide more information about the user or to enhance productivity and successful results for information workers. Come see some demos and hear about Microsoft Research team’s vision.

Speaker – Andrzej Turski, Principal Software Development Engineer, Microsoft Research
Speaker – Jonathan Grudin, Principal Researcher, Microsoft Research

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!

I attended the Maker Faire down the hill in San Mateo at the County Fair Grounds.

The event is the gathering of the many forms of craft, tinkering, building, mashup, hacking, and experimental communities.

Here are some photos from today’s event.

My highlights: the full sized replicas of TV and movie robots from Lost in Space and Forbidden Planet; the littlebits snap together circuits, the LED bicycle wheel displays, the Telsa coils (of course), the flame throwers (of course), and the rolling metal ball robots.

It was a well attended event with many great displays.

Some highlights:
An Examination of Language Use in Online Dating Profiles
Meenakshi Nagarajan, Marti Hearst

Event Detection and Tracking in Social Streams
Hassan Sayyadi, Matthew Hurst, Alexey Maykov

Gephi: An Open Source Software for Exploring and Manipulating Networks
Mathieu Bastian, Sebastian Heymann, Mathieu Jacomy

Information Diffusion in Computer Science Citation Networks
Xiaolin Shi, Belle Tseng, Lada Adamic

Considering the Sources: Comparing Linking Patterns in Usenet and Blogs
Mary McGlohon, Matthew Hurst

[Vladimir Barash is liveblogging the ICWSM conference]

10.30am A categorical model for discovering latent structure in social annotations (Said Kashoob)
Given a collection of web objects, users and tags, can we model the underlying tag generation process?

-Discover implict communities of interest?

-Categories of related tags?

-For given category, id most relevant objs for category

-compare categories

Initial thoughts: content-based topic modeling (Latent Dirichlet Allocation, LSA). Recent work applying LDA models to tags (Wu 2006, Zhou 2008)

Modeling social annotations: the process that generates content is fundamentally different from the annotation process (many authors per “document” = tag collection, not aware of each other)

Community based categorical annotation model (CCA). Communities are groups forming around interests, etc. Each community has a number of categories as its world-view. For each object, a community draws tags from the appropriate underlying categories

Object annotations are generated by communities. Each community selects tags from its category set.

-use Gibbs sampling to recover a joint distribution of tags, categories and communities

-can do inference to find most likely tags per category, per community

Content-based topics vs. tag-based categories

Exploring content vs. annotation: for pairs of objects that are similar in category space, how topically similar are they? Reslt: objects with similar content do not necessarily have similar tags and vice versa

Rubix cube example: objects similar both in category and topic are solutions to the puzzle, objects that are only similar in category are puzzles / games, objects that are only similar in topic are math pages

11am Content-based summarization and categorization in the blogosphere (Ahmed Hassan)

How can we decide which blogs are more important / influential? Given a set of blogs related to a particular topic, find a subset of blog feeds to read that have continued interest in the topic.

Can we use hyperlink popularity based algorithms for speeches and blogs? Yes, but they might not work very well

Use textual similarity to link posts instead of hyperlinks: maybe blog A affects blog B? Given a set of blogs, build a graph where nodes represent posts/feeds and edges link posts/feed with simliar text

Use a pagerank-like measure to calculate importance score of a blog in the similarity network

How can we select nodes that are important but diverse? Add discounting factor based on similarity of node to neighbors

dataset: TREC blog datase

Evaluation: use linear threshold diffusion model! How many blogs covered (activated) by first k blogs in rank. Also split data by time to see how valid is rank(t) for predicting coverage at t+1. Approach also does a little better at precision-at-k on the TREC blog dataset

11.30am Supervised ranking of syntactic configurations for finding targets of semantic expressions (Jason Kessler)

Trying to find targets of sentiment phrases (“while the dealership was friendly, the *car* was a disappointment”)

Sentiment expressions only link to physical targets (“Bill likes to drive the car”)

Two-domain corpus: cars and camera

Baselines – proximity, one-hop with dependency parser

Approach – learn to target from a corpus. Supervised ranking instead of classification. Uses linear-kernel RankSVM, off-the-shelf approach

Results – supervised ranking does better than proximity, one-hop, approaches interannotator agreement

Future work: inter-sentential target

3pm Stochastic models of user-contributory web sites (Tad Hogg)

Focus: describe aggregate group behavior

-determines structure and usefulness of user-participatory sites

Models enable:

-predicting user behaviors

-incentivizing user participation

Stochastic modeling summary:

-Start with individual user behavior, specify states and transitions between states

-Determine collective behavior (details in paper)

Illustration: Stochastic Model of Digg

-Phenomenology: users submit and vote on news stories, Digg promotes popular stories to front page, allows social networking (friends, fans)

Model of Digg voting behavior: visibility and interestingness -> votes. Extension to prior model (Lerman ’07).

- “law of surfing” for viewing web pages (Huberman et al. 98)

- incremental average growth in number of voters’ fans

- construct equation for dynamics of vote volume for a story from state diagram that formalizes visibility and interestingness. Params for vis and interest estimated from story sample. Estimate viewers watching stories from models and data.

Data: front page and upcoming stories since May 06

Modeling story visibility: story location, navigating web sites, number of fans. Each voter enables fans to see story via friends interface.

Modeling story interestingness: topic, novelty, popularity. Can estimate from web-based experiments, e.g. Salganik et al. 06, but can estimate from models and data.

Results: model captures qualitative features – slow growth initially, influence of fans on promotion, rapid growth if story promoted (much more visible to users)

Results: the number of fans have not yet seen the story drops, number of votes on story grows significantly after story gets promoted. “Promotion line” in number of fans / interestingness splits stories into will be / won’t be promoted with 95% accuracy

Predictions from early behavior: can predict #votes from first 4 votes (similar to results for YouTube), but “law of surfing” and incremental growth important parts of model

Conclusions: stochastic process approach connects user and system behaviors, applicable to social media in general when users have limited information and actions, limited use of personalized history.

3.30pm Personal information management vs resource sharing: towards a model of information behavior in social tagging systems (Markus Heckner)

Why do people tag?

Tagging: a fourth layer of indexing? (On top of author keywords, intellectual indexing by information professionals, and auto-tagging)

media type influences tagging: differences in number, language, function of tags btw Connotea, Flickr, YouTube, Delicious

Method: Scientific crowdsourcing using Mechanical Turk

Assumption: Different motivations for taggs

-Organization of one’s own digital content, i.e. personal informational management (Delicious, Connotea), vs. information sharing (Flickr, YouTube)

Questionnaire Design: Question Types

-online questionnaire posted as “human intelligence task.” asks general information, general motivation, tagging motivation and understanding, social bookmarking and search, recent usage.

Data: ~150 subjects, users of Flickr, YouTube, Delicious, Connotea

Results:

Motivation: YouTube is significantly weaker-motivated for PIM, Delicious much weaker for sharing, Flickr and Connotea about even

Perception of tagging: Connotea users perceive tagging as most easy, follow by YouTube, Delicious, Flickr (not significant). Connotea user agree very strongly that tagging is a useful feature

Towards a model of tagging behavior: Shneiderman’s approach towards social software (social spheres), etc.

4pm Motivational, structural and tenure factors that impact online community photo sharing (Oded Nov)

Why do people in online communities share? Can we quantify the drivers for sharing (or not sharing) and their effect on actual behavior?

Three types of questions as framework:

Why – drivers of sharing (Motivation, structural properties, personality, privacy concerns)

What – type of information shared (code, content/facts, meta-info (tags), photos)

Where – context of sharing (OSS, Wikipedia, Flickr)

Creation vs. sharing: the act of sharing is separate from the act of creation

People take photos regardless of the sharing act (really?), the “second act” of sharing photos is optional, separate from the “first act” of photo sharing

Identifying the factors in sharing: motivational (extrinsic vs. intrinsic), structural factors (position of user in community network), tenure in community

Motivations: enjoyment (self/intrinsic), commitment to the community (others/intrinsic), self-development (self/extrinsic), reputation (others/extrinsic)

Response variable: artifact sharing per tenure year, IV: motivational vars + structural (number of contacts) + tenure (years since started sharing)

Method: combine user-reported (survey) data and system data: what people say + what people do. N=278, used only “pro” users (>200 photos) with at least 3 months’ tenure on Flickr.

Results: significant positive effect of commitment, negative of self-development, positive of number of contacts, negative of tenure, rest not significant.

Why is enjoyment not correlated with sharing? Users may be motivated more by “fun” of creation rather than content sharing.

Why is correlation between self-development and photo sharing nefative? A tradeoff between contribution quality and quantity? Greater self-development motivation -> focus on the quality of artifacts shared, at the expense of quantity

Summary:

quality / quantity tradeoff, fun is not an issue?, diminishing sharing

4.30pm Modeling Blog Dynamics (Michaela Goetz)

Blogosphere is a system of interactions: Entities: Bloggers, Posts, Topics

Model: simple set of rules (followed by blogger) that creates these interactions

Evaluation: creating a synthetic blogosphere, comparing it to real blogosphere

Motivation: forecasting, advertising

How is this different from modeling social network? 2 networks combined: Blog vs. Post network, complex temporal dynamics

goal: model micro-level interactions to observe macro-level interactions in blogosphere

Properties of the blogosphere:

-Topological – blog, post = follow power law distribution

-Temporal – user posting activity, popularity over time (link creation)

Burstiness (Slope = 1 of aggregation level vs. entropy) & Self-similarity (Linearity of aggregation level vs. entropy)

Inter-posting time follows a power law

Time t vs. number of in-links t days after publishing follows a power law

Desired model: simple (no parameters), intuitive (local rules), creates realistic topology and dynamics

First-try solution:

-inter posting times sampled from exponential distribution, links created using pref attachment – leads to exponential inter-posting distribution, poisson degree distribution (really?), etc.

Second-try solution (Zero-Cost):

In every round, for every blog, user u takes a random walk step, if he reaches 0, he decides to post P

when he posts, he can make a link or not, if he makes a link, he can choose a neighbor based on frequency of links or non-neighbor, then chooses some post of neighbor and links to random posts upward in the cascade

This model accurately reproduces both the topological and temporal patterns (at a qualitative level – same distributions, different though relatively close exponents. Biggest difference: 1.5(sim) vs. 0.7(real) in inter-posting time exponent)

[Vladimir Barash is liveblogging the ICWSM conference]
9-10AM: A Tempest: Or, on the Flood of Interest in Sentiment Analysis, Opinion Mining, and the Computational Treatment of Subjective Language (Lillian Lee)

-Sentiment analysis using discussion structure: clasify speeches in US congressional floor debates as supporting or opposing proposed legislation -Individual doc classifier -agreement (degree) classifier for pairs of speeches

-Agreement info allows COLLECTIVE CLASSIFICATION – “agreeing speeches should get the same label”

-ECON: debate about effect of sentiment on sales
-comScore (users willing to pay 20-99% more for 5 star item vs. 4 star item)
-Jury is still out

-SOC: What opinions are influential? (Niculescu-Danescu Muzyl et al.)
-Prior work has focused on features of text and has not been in context of sociological aspects of reviews
-look at helpfulness scores

-What about review’s star rating in relationship to others?

-theories from soc / social psych:
-conformity
-brilliant but cruel

-Are the social effects just textual correlates?

-would like to control for actual quality of review text. Manual annotation? Tedious, subjective. Automatic clasification? Need extremely high accuracy guarantees.

-use plagiarism (1% of all reviews) to control for text quality! findings hold for plagiarized pairs

Summarizing:

-Sentiment analysis has many important applications – to researchers, to citizens, to governments

-encompasses many interesting research questions

-extends to many areas

Stand-out question: matt hurst and the user as generative model for opinions

10.30 AM: Gesundheit! Modeling Contagion through Facebook News Feed
(Eric Sun, Itamar Rosenn, Cameron Marlow, Thomas Lento)

Motivation: how do ideas diffuse through a large social network?

-Theory of the Influentials (Gladwell)

-Accidental Influencers(Watts): anyone can be an “influencer.” Ideas don’t spread via influentials, ideas spread like viruses (susceptible or not), goal to find a large number of susceptible people

Q: are contagions triggered by small # of sources? What are some characteristics of diffusion chains on Facebook? Can we use demographic or behavioral characteristics to predict size of diffusion chains a particular user will create?

Spreading ideas on Facebook – through News Feed

-Page Fanning = becoming fan of people, orgs, etc.

-Mechanics: Alice fans a page, Bob sees Alice’s action on his News feed, Bob fans page as well (link: Alice -> Bob)

-Strong ties: links depend both on friendship and on actions (following)

-Median page has most of its fans in one (weakly) connected cluster

-Large clusters Not Started by “one guy” – roughly 15% of fans in the biggest cluster of each Page are start points

-Variability in this percentage becomes very small as #fans increases

-Clusters are formed when many short diffusion chains merge

-Data: actor to follower connections for ~300,000 FB paes

-Main dataset: page-level data

-Second dataset: select 10 random, representative pages (at least 40 days old had at least 5k fans) and analyze users that start chains

-Prediction Model: Response = max_chain_length, Predictors: gender, log age, log FB age, etc. Method: 0-inflated neg binomial regression

-results: Demographic characteristics not important, number of Facebook friends not important, feed exposure is the strongest predictor with coefficient ~ 1 (so a 1% increase in the number of people who see ego’s fanning ~ 1% increase in chain length)

-Comment: this is global focus, not local focus. What about the interpersonal dimension, i.e. the likelihood that Alice infects Bob?

-Comment: support for Duncan Watts’ idea

————————————————————————————————————————————————-

11am Seeking and Offering Expertise across Categories: A Sustainable Mechanism Works for Baidu Knows
(Jiang Yang, Xiao Wei)

Baidu Knows: Chinese QnA site

-Growing extremely fast: more than 80 million questions asked in 4 years.

-Huge user population (2.6 mln users). Knowledge repository as online source

-Points! Points! Points! (flexible amount of extra points set for best answerer, more points buy more answers, etc.)

-Building sense of community: honor title system (including traditional Chinese titles!), online chats, etc.

-Data: Full history of QnA 12/07-05/08. 9.3 mln questions asked, 5.2 mln (56%) resolve, 2.6 mln users participated

-3.3 answers for each question (vs. 7.3 for Yahoo! Answers, note that Yahoo! Answers encourages answering more than asking)

-Significant categorical difference in awarded points: low(brand, science, food) vs. high (medicine, computer, music)

-Price of answering positively correlated to popularity of category

-Order difference: according to human rating of sample questions, order of answers doesn’t matter, but first answer has highest chance to be best answer, more points awarded for later best answers

-Reinforcement cycle: encourage continuing

-Answerer performance positively correlated with activity level. More active answerers choose less expensive questions, questions with fewer answers. More active answerers working harder (longer answers), and more focused (on particular category)

Reinforcement cycle: choose less competitive q’s -> better performance -> more efforts -> more focused -> choose less competitive q’s

-Askers: learn how to better ask: more active askers, ask cheaper questions, experienced askers get more answers with per point they ask (slight trend).

-Asker/Answerer hybrids (22% of pop): core of contribution! Much more active (almost 1/2 total questions), more generous (offer higher award: 12.3 per question versus 11.6 on average in general, share same pattern as normal asker but paying higher each time), not necessarily experts, incentivized

Seeking and offering across categories: some categories are pretty self-contained, others are more porous. Lots of cross-category contribution

-A sustainable mechanism is working on Baidu Knows (that’s a good discussion question!)

11.30 AM: Community Structure and Information Flow in Usenet: Improving Analysis with a Thread Ownership Model (Mary McGlohon, Matthew Hurst)

-Compare communities of online social nets may lend insight into how groups form and thrive

-How does info diffuse between communities?

Data: Usenet, 200 politically-oriented newsgroups (bulletin boards) – polit in name, Jan 04 – june 08. several countries, 19.6 mln unique articles, 6.2 mln cross-posted

Cross-posting: large % of articles are cross-posted to multiple groups. Somebody reading one group may “reply-to-all” such that all groups see it.

Structural analysis: how do edges btw authors form? How does the reciprocity of groups compare? How can we measure similarity btw groups?

-Make network of authors for each group, if a_1 has replied to a_2 at any point, there is an edge from a_1 to a_2. Find power law relationship btw #of nodes and #edges over time (similar to Leskovec et al. densification). Exception: tw.bbs

-Reciprocity: which groups have highest reciprocity? Top 10 were European newsgroups, e.g. hun.politika (up to .58). Lowest reciprocity: tw.bbs

-Similarity: use Jaccard coefficient for cross-posts = #shared articles btw 2 groups / Total # articles in groups, can do same with shared authors

Highest similarity ~.54 (bc.politics and on.politics).

Draw thresholded similarity network, find clusters: parties, US regional, countries, alt.politics subgroups

-Image: english-speaking countries cluster. Can.politics (Canada) highly central!

Ownership Model: we would like to find out in which group the activity is truly occurring. How can we trace this? ANswer: assign “ownership” based on authors of posts. First, assign authors to groups based on devotion, where devotion(a,g): what % of an author a’s posts are exclusively posted to a given group g

-For all groups that author posts particular post p to, the post belongs to the group with the highest (normalized) ownership between it and the author

-Example: “Kiss the National Parks Good-Bye” initially corss-posted to several groups, 38 groups in total, ownership concentrated in seattle.politics and or.politics

Information flow between groups: How often does an author in group 1 respond to a post in group 2? Define influence g_a, g_b as the product of the groups’ devotion scores for a particular author

Ownership-based similarity. Q: How can ownership help us more precisely state when 2 groups are similar? Use devotion instead of Jaccard to calc similarity between groups

-Potential applications: link prediction, IR and relevance, ownership for email lists. Future work: use ownership to predict whether group will continue or die off

1.30pm Does Showing off Help to Make Friends? (Christophe Aguiton)

Self exposition and social capital:

-What do we let others see about ourselves on social networking sites?

-How do we relate to others depending on what they show?

Game sociological survey: link

part 1: if you were on these pics, which would you publish on a website?

part 2: questionnaire

part 3: down-to-one-friend (start with x friends, see pics only, eliminate one; add favorites info, elminate one; etc. down to one friend)

first launch: FB, diffuses to blogs, Flickr, news, 15,000 respondents by end of experiment.

-Sample is not representative of French SNS users. Lots of heavy internet users. 71.1% male, average age 28 years old, 47% high school diploma, 33% students.

First Results:

-moderate / controlled level of exposure (exposure score: ~2.4 on 1-4 scale)

-extraversion index, socializing index

Method: PCA to cluster photos in the experimental dataset. Four components: traditional self-exhibition (ordinary life situation), bodily immodesty (nudity / sexual situations), showing off (protests, etc.), provocative (negative activity).

-Cluster analysis with scores of PCA, five clusters: Modest (people don’t like to show themselves, 19%, more women, older, high level of ed, high status position, few friends) + four from above.

-Main question: find no correlation between sns use and level of self-exposition

-2nd question: how do people make friends?

- popular friendship targets (from 3rd part of game) are young, cool, active, unpopular are  older, more reserved

- subject choice largely guided by homophily, a tendency to bond with similar others. Results: people preferentially choose as friends of same age and diploma level. Heterophily by gender: both men and women choose women over men.

- What aspects of persona do different kinds of people look at? Modest people most closely look at “about me,” traditional exhibitionists most closely look at “wall,” provocative most closely look at “sexual preferences”

Main results of survey:

-Self-exposition on web is a social construction, requires reflexive and strategic control of one’s image, self-exhibition strategies differ according to sociological factors, social networks encourage homophily but also allow users to have more heterogeneous social capital

2pm. What are they blogging about? Personality, topic and motivation in blogs (Alastair J. Gill et al.)

How does personality influence blogger motivation?

Personality – describes fundamental core of individuals

-Behavior and preferences

-Useful for categorising users and consumers

-How does this influence bloggers? Blogs – unique freedom of expression for authors

-Already shown to influence langauge in CMC (Gill 2004, Nowson 2006).

-Analysis of Polish blogs w/ suggested psychological profiles)

Motivations: Internal – Documenting life, catharsis (therapy); External using own perspective – Interests, Opinions

Personality: Big Five model of personality (Goldberg ’92, Costa and McCrae ’92).

Data and Method: Internet meme personality test: 5 Y/N questions each for the Big Five personality types -> high-mid-low scores; 3 months of blogs extracted from Nielsen BuzzMetrics data. Basic statistics, text analysis.

results:

Neuroticism: use of blogs for self-therapy/catharsis – focusing on self and venting purely negative feelings

Extraversion: life narrative (documentation) in conversation with reader; expressing highs and lows, but not mundane. Use of 2nd person pronouns

Openness: review or evaluation of leisure (music, TV) from personal perspective, but no increase in thinking or senses

Conscientiousness: faithfully document life going on; references to others; positive emotion. Job focus, little temporal narrative.

Agreeableness: positive self-talk focus

Discussion: Blogs unsurprising mainly focus on self. Face apparently genuine in blogs. Agreeable bloggers provide a barometer of what is / isn’t acceptable in blogs

2.30pm A social identity approach to identify familiar strangers in a social network (Nitin Agrawal)

Who are familiar strangers?

Observe repeatedly, but do not know each other: Real world – people you see daily on a train (going to same workplace); Blogosphere – people who have similar blogging behavior / interests but not in each other’s social networks

Together, familiar strangers form a critical mass: understanding of one blogger gives a sensible and representative glimpse to others -> better customization, personalization and recommendation.

Familiar strangers in social media: an example, u is a blogger with interests A_u, friends v_1… v_k with interests A_v_1… A_v_k. Find non-adjacent u’ with similar interests (intersection of A_u, A_u’ is non-empty).

-Egocentric network view (exposure to network limited to neighbors).

-Social identity approach: cluster contacts into groups, propagate search through relevant clusters of contacts (prunes search space). For this to work, network needs to be a small world (WS 98)

-Method: represent contact by tag vector, content vector, use cosine similarity, then k-means clustering

-Ground truth: Global network view. Data: Blogcatalog (~24k nodes), DBLP (~35k nodes). Also compare to exhaustive and random search strategies.

Results: 79.3%+-3 for BlogCatalog, 91.3%+-2.1 for DBLP, greatly reduced search space.

3pm You are where you edit: Locating Wikipedia Contributors through Edit histories (Michael Lieberman, Jimmy Lin)

Minig Wikipedia: id Wikipedia contributors who edit geopages in a constrained space, have specific “pet” geopages (pages for geographical locations identified with geotags)

Features with extent: all geopages tagged with single lat/lon, even though they can be countries, cities, rivers, etc.

Wikiepdia edit histories: ignored anon edits, minor edits, focused on edits to geopages

Edit area = convex hull of geotags smaller than 1 degree sq. Account for outliers with simple approximator that cuts off at F closest-together geotags

Results: Pet Geopages. Over 50% of contributors with 5-20 edits, and 25% of contributors with over 20 edits, have 80% of edits to 1 or 2 geopages

Reasons for Tight Edit areas: randomly selected 100 contributors with at least 10 edits to geopages and small edit areas. Concurrently examined contributors’ user pages and the set of edited geopages to determine an interest. Contributors with small edit areas tend to be born in or are living in close-to-edit areas.

Future work: using alterante measures to determine geopage edit significance

4pm CourseRank: a closed-community social system through the magnifying glass(Georgia Koutrika)

CourseRank: community for Stanford students to evaluate courses, browse courses, plan academic program, interact with each other, ask / answer questions. 1.5 years, 11k students, 19k courses, 3k reviews

Special features: well-defined closed community, multiple constituencies (staff, students), special-purpose tools, hybrid data

A new class of social sites defined by these characteristics. E.g. university social site, scientific social site, A-space (intelligence)

Popularity: >85% of Stanford students are CourseRank users

Usage: follows academic cycle

Participation inequality: 20% created by intermittent, 80% by active; 31% of lurkers, 38% intermittent, 30% (!) active

Smaller communities (departments) breed more active students

Truths and Lies: grade distribution follows official. Good incentives make better users (is this really evidence?). But there is bias: correlation between grade given to student and rating given by student

Lessons Learned:

-added-value services a big thing

-high-quality data

-community feeling is strong = students coming together with common need

-meaningful incentives

4.30pm Using transactional information to predict link strength in online social networks (Indika Kahanda)

OSNs (Online Social Networks) are larger and more heterogeneous than manually-collected social networks

High median degree implies presence of many weak links

Conjecture: Link strength can be predicted from transactional information

Data: Purdue FB. Transactional info: Wall comm, photo postings, group memberships. Networks over Wall, Pictures look more like offline-collected networks (e.g. AdHealth data)

Automatically identifying top friends: link strength prediction task (binary)

Related to, but different from, link prediction (which focuses on predicting future links between u,v in a unimodal network). Previous approaches use attribute similarity features or topological features of network. Adamic and Adar (’03) used ancillary networks but focused on similarity vs. transaction

Feature types: Attribute-based (attribute similarity btw two nodes), Topological features (assess connectivity of users in friendship network), transactional features (number of bi-directional wall/photo/group posts), network-transactional features (assess connectivity of users in transaction networks)

Experiment 1: Feature rankings. Compare relative importance of each of 50 features, using info gain and chi-square statistic. 12 of top 15 are network-transactional features, 3 are transactional, 12 use wall info, 3 use picture info.

Experiment 2: Feature type comparison. Ablation study. Network-transactional features achieve best performance

Experiment 3: Link type comparison. Ablation study using data from each link type separately (all features). Wall information results in best performance. Picture info does not improve performance because of sparsity

Experiment 4: overall classification results. Bagged decision trees perform best.

Results indicate that transactional events useful for presenting link strength, but should be used in context of larger network for best performance

5pm RevRank: a fully unsupervised algorithm for selecting the most helpful book reviews (Oren Tsur)

Most reviews are: repetitive, limited contribution, poorly written, unnoticed

User voting bias: Liu et al. – imbalance vote bias, early bird bias, winner circle bias. Many very helpful reviews go unnoticed.

Interesting features of reviews:

-there are a lot of them

-contributors put big cognitive effort to generate them

-Good faith. Reviewers expect no direct reward.

Main idea: automatic detection of dominant concepts. Dominant concepts are either really frequent or infrequent but very informative. Term dominance defined as ratio of term frequency in review set to term frequency in balanced review set (British National Corpus)

RevRank algorithm: find most dominant concept, vectorize, rank reviews according from centroid identified by the core vector

Experimental setup: 12k reviews for Da Vinci Doe, World is Flat, Harry Potter, Ender’s Game. Compared to random, user votes. Gold standard – human labels.

Results: in 85% of test batches, RevRank pick was ranked “the most helpful.” In some cases, random algorithm outperformed user votes!

Summary: RevRank is fully unsupervised, better than user votes, finds “hidden” reviews and interesting insights

End of Day 1

On Tuesday night Marc Smith and I will be presenting the poster for our paper, “Distinguishing Knowledge vs Social Capital in Social Media with Roles and Context” at the International Conference for Weblogs and Social Media. You can find the poster, co-authored with Marc Smith (Telligent Systems), Lise Getoor (University of Maryland) and Howard T. Welser (Ohio University), here. The full text of the paper has more information, but the poster is a good summary of the key concepts in the paper:

• What roles do people play in social media?
• What contexts shape user behavior in social media?
• How can we leverage roles and context together to predict future user behavior (in terms of contribution type) from past user behavior?

The specific research question being addressed is: can we predict whether a particular contribution to Live Q&A (a Microsoft-sponsored community question answering site) will be contain factual information, or discussion / chat. It is possible to do the prediction based on the text of the contribution, but such an approach focuses entirely on the content, and not on the actor – the user who is making the contribution. If we leverage actor-centric information (what role does he/she play in the community: an “answer person” or a “discussion person”? is he making the contribution in a discussion-oriented context, such as implied by tagging the contribution as “fun,” or a fact-oriented context, such as implied by tagging the contribution as “math”?), we find we can build a decent predictor at very low cost with very few variables. If we use just role information or just context information, we do reasonably well… but if we use both, we do *much* better. While the question we’re answering here is quite specific, the advantage of our approach is that it can be applied to almost any social media context – any place online where users can both contribute content and interact with others. We could just as easily create a predictor for contributions to Yahoo! Answers, or even to Wikipedia (if we had the relevant data). This is definitely food for thought / opportunity for future work

I will lead a workshop with Martha Russell on social network analysis of social media as part of the Stanford Media X Summer Institute on New Metrics for New Media: Analytics for Social Media and Virtual Worlds this Summer.  I am looking forward to working with the folks at Media X which hosts a range of cutting edge events devoted to exploring the newest trends in technology and society.

It is also worth noting that the traveling exhibit “Places and Spaces” will be displayed through the MEDIA X program at Stanford until December 18th, 2009.  There is a May 18, 5-6:30pm Reception in Wallenberg Hall on the campus.  The show includes an image I worked on with Danyel Fisher and Tony Capone that represents an overview of Usenet newsgroups.

The show includes a variety of information visualizations and maps that illustrate the utility of graphical representations of complex concepts and terrains.  From the Media X site:

“The Places & Spaces exhibit, at Wallenberg Hall has two components. The physical component is available for display and allows for close visual inspection through high-quality prints. It is meant to inspire cross-disciplinary discussion on how best to track and communicate human activity and scientific progress on a global scale. It includes hand-on science maps for children. The online counterpart provides links to a selected series of maps and their makers along with detailed explanations of why these maps work.” [Link]

There will be a reception following the May 18 Seminar that will include Jeff Heer and students, Katy Borner (virtual presence) and other mapmakers of the Places & Spaces exhibit.

Eduarda does a great job demonstrating the ease with which a sophisticated analysis can be implemented via the NodeXL interface.

NodeXL is about to cross 8,000 downloads and has several releases in the works to add better tools for laying out a social network diagram.

This year’s CITASA awards have been announced!  CITASA is the Communications and Information Technology section of the American Sociological Association.  It gathers together more than 300 sociologists interested in the ways groups of people make use of computation and networks. This year the line up is uniformly high quality scholarship about the nature of societies that increasingly rely upon information technology.

You are welcome to join the CITASA Business Meeting on Aug 8 from 9:30-10:10am at the Parc 55 Hotel where the recipients will be presented with their awards. A description of the awards and list of past recipients can be found on the CITASA website:  http://citasa.org/awards

2009 CITASA Student Paper Award

Daniel A. Menchik and Xiaoli Tian (University of Chicago)

Putting Social Context into Text: The Semiotics of E-mail Interaction. American Journal of Sociology 114(2): 332-370. (2008).

Committee members: Zeynep Tufekci (Chair), Lori Kendall, and Anabel Quan-Haase

2009 CITASA Award for Public Sociology

Peter Kollock (University of California at Los Angeles)

Committee members: Michael Macy (Chair), Marc Smith, Keith Hampton

2009 CITASA Paper Award

Eszter Hargitta, Jason Gallo, and Matthew Kane (Northwestern University)

Cross-ideological discussions among conservative and liberal bloggers. Public Choice 134: 67-86. (2008).

Honorable mention:

Lori Kendall (University of Illinois at Urbana-Champaign)

How do issues of gender and sexuality influence the structures and process of qualitative internet research? pp. 99-118. In Internet Inquiry: Conversations about method, Annette Markham and Nancy Baym (eds). Los Angeles: Sage (2008).

Committee members: Hiroshi Ono (Chair), Rich Ling, and Bernie Hogan

2009 CITASA Book Award

Tarleton Gillespie (Cornell University). (MIT Press, 2007).

Committee members: Leslie Shade (Chair), Marc Smith, and Alison Powell

2009 CITASA William F. Ogburn Career Achievement Award

Elihu Katz (University of Pennsylvania)

Committee members: Anabel Quan-Haase (Co-Chair), Barry Wellman (Co-Chair), and Keith Hampton

Our (Vladimir D. Barash, Marc Smith, Lise Getoor, Howard T. Welser ) poster paper, Distinguishing Knowledge vs Social Capital in Social Media with Roles and Context  has been accepted and published at the 2009 ICWSM (International Conference on Weblogs and Social Media) conference which will be held in San Jose, California this May 17, 2009 – May 20, 2009.

Abstract
Social media communities (e.g. Wikipedia, Flickr, Live Q&A) give rise to distinct types of content, foremost among which are relational content (discussion, chat) and factual content (answering questions, problem-solving). Both users and researchers are increasingly interested in developing strategies that can rapidly distinguish these types of content. While many text-based and structural strategies are possible, we extend two bodies of research that show how social context, and the social roles of answerers can predict content type.  We test our framework on a dataset of manually labeled contributions to Microsoft’s Live Q&A and find that it reliably extracts factual and relational messages from the data.

Full Text: PDF: 2009 ICWSM Distingusihing knowledge versus social capital

Princeton Center for Information Technology Policy

I attended the “Studying Society In A Digital World” conference at the Center for Information Technology Policy at Princeton University.  They just posted most of the conference slides.  I took some pictures and have inserted them next to the link for slides where I had a picture (or a good one!).  The conference was very useful and informative: there is a great trend towards sensor driven data sets that, in aggregate, illuminate large complex systems in detailed and surprising ways.

Talks from SenseNetworks and MIT made the vision of a continuous “trail” document assembled by location and biological sensors from every human on earth seem not so outlandish. Samuel Madden from MIT spoke about opportunistic mobile wifi connectivity in moving vehicles.  MIT rebuilt the WiFi stack to enable 13ms associations instead of 13 second associations with an access point.  The result is that a car with such a WiFi card can drive along Boston city streets and exchange about 200KB a minute with open unsecured access points along the way.  Free bandwidth in the city.  What do they do with it?  They stream live telemetry of a fleet of cabs.  The cabs have accelerometers on them and GPS which is reported in almost real time back to a server.  Along with the engine computer’s data, they collect a ton of data about traffic and road surface quality.  They can see changing patterns in the activity levels of the cabs and infer changing activity at businesses.

A major theme of several presentations was crowdsourcing for science, with talks about ebird.org and galaxyzoo highlighting a distinction between sites that enable a group to collect data (ebird) – with the associated issues of data validity — and those sites that enable a group to annotate data (galaxyzoo) that has already been expertly collected.

Lada Adamic: Social Influence and the Diffusion of User-Generated Content

Chris Barrett: Co-evolution of Sociotechnical Networks and Individual Behavior

Kathleen M. Carley: Information & Belief Diffusion Through Social Networks: Empirically Grounded Simulation

Damon Centola: New Theory and Experiments on Diffusion in Social Networks

Pablo Chavez: The Current Policy Debates Over Online Information Practices: Implications for Research in the Digital Age

Nosh Contractor: Digital Traces: An Exploratorium for Understanding & Enabling Social Networks

Nathan Eagle, Michael Macy: Scaling of Sociodynamics

Scott Golder: Temporal Rhythms in Electronic Society: Examples from Facebook and Elsewhere

Eric Horvitz: Through the Lens of a Large Instant-Messaging Network: Planetary-Scale Views on Behavior

Tony Jebara: Learning Networks of Places and People from Location Data

Steve Kelling: eBird: The Long Tail of Community Engagement in the Scientific Process

Jon Kleinberg: Spatial Signatures of On-line Behavior

Robert Kraut: Theory-Based Design of On-Line Worlds

W. Russell Neuman: Social Science and Policy Praxis

Jukka-Pekka Onnela: Using Cell Phones to Study the Large-Scale Structure of Social Networks

Paul Resnick: Understanding Opinion Diversity Preferences Through Field Experiments

Matthew Salganik: Community-Generated and Community-Sorted Information In his presentation Matt made the remarkable connection between deliberative democracy and the cat comparrison site: Kitten Wars.  His talk introduced a model for a kind of Am I Hot or Not for political discussions.  His group built a web site that helped the student community at Princeton set its priorities for student government.  The work has significant implications fo deliberation tools for organizations and enterprises.  Unlike systems that simply encourage users to contribute ideas to a potentially long and never acted upon list, this system forces a comparison task that can be performed in one click but demands implicit contrasts and estimation of value.  The use of the almost adictive “hot or not” style interface (or more accurately, kittenwars)  allows users to decide between, for example, longer hours for the student cafeteria or expanded video rental services, and get presented with their estimate in the context of other’s choices and the opportunity to choose between two things again.  After a population has run through a set of pair-wise contrasts a broader sense of the priorities of the community can be calculated.

In my talk, I focused on the idea that information want not to be free or expensive, rather, information wants to be copied.  Like DNA, the goal of any string of bits is to make a duplicate copy of themselves.  Several technical realities mean that while information may exist on a spectrum from private to public, it only moves in one direction (public) and almost never back.  Once made public on the Internet, even if only for a moment, a photo, document, or other digital object is almost certainly to have been copied, indexed, backed up, or replicated.  All efforts to delete a digital object once widely distributed is like trying to take wine out of water.  This is because all cryptography become brittle over time, most bits end up exposed after they get distributed, and more events trigger widespread distribution of bits than expected (for example, linking a photo, and a location, to a tweet that gets copied to LinkedIn and Facebook, that then appears in an RSS feed and is copied from there to Friend Feed.  As it travels, information looses more of the access controls that initially made it relatively private until it is effectively public.

Marc Smith talks about information at Princeton CITP "Studying Society in a Digital World" Conference - Photo Credit: Scott Golder

Marc Smith: Autobiography, Mobile Social Life-Lagging and the Transition from Ephemeral to Archival Society

Joshua Tauberer: Watching the Watchers: Government Oversight with Civic Hacking

Marshall Van Alstyne: Information, Social Networks and Productivity

Sadly, no picture for Luis Van Ahn’s talk: however, this presentation was a fascinating review of the capcha and re-capcha services and the new direction of providing translation services as language learning games.  Luis Van Ahn invented capcha, felt bad about the cumulative human time wasted by filling out those squiggle word puzzels to get on a web site, and decided to harness capchas to a useful task: text recognition for books.  To translate words from bad scans of books that the OCR software fails to recognize correctly, the garbled data is presented to humans, who, collectively, have translated millions of previously unintelligible words.  Now, his new project is to expand the small user population of bi or multilingual speakers who can translate between languages.  The approach applies the “Mechanical Turk” “human intelligence task” concept to language translation.  His language translation service presents foreign language sentences to users with all dictionary words from a simple translation listed below.  Users click on best word selection beneath each foreign word.  The surprising results: pretty good translations AND users start learning a foreign language!

Luis von Ahn: Human Computation

We got some great questions from the attendees about how they can apply these approaches to their social media investments.  Tools like NodeXL can be helpful for people interested in structural data analysis.  Kate has built tools for performing semantic analysis of social media content over time.

The video is now available on vimeo:

Beyond Buzz: On Measuring a Conversation (Web 2.0 Expo 2009 – Katie Niederhoffer & Marc Smith) from Steffan Antonas on Vimeo.

Another conference focused on research on blogs and other forms of social media is “ICWSM” – the International Conference on Weblogs and Social Media.  I was able to attend the previous meeting of this conference last March in Seattle and give a talk about different classifications of social media and I am looking forward to attending this year’s meeting in San Jose.  Last year we had a poster paper in the conference about the ways some users in a blog system called Wallop were able to hold other users in the system.

Some Users Pack a Wallop: Measuring the Impact of Core Users on the Participation of Others in Online Social Systems
Thomas M. Lento, Eric Gleave, Marc A. Smith, Howard T. Welser

There was also a paper about the lessons learned from managing large corporate online community efforts.

Space Planning for Online Community
Danyel Fisher, Tammara Combs Turner, Marc A. Smith

This year, we have a poster in the conference that is focused on the ways network structures created when people reply to one another can be used to predict whether a message or thread is a question and answer exchange or a long discussion or debate.

Distinguishing Knowledge vs. Social Capital in Social Media with Roles and Context
Vladimir Barash, Marc Smith, Lise Getoor, Howard Welser

The conference attracts some great people and features the state of the art in research at the intersections of computer science, natural language processing, social network analysis, search engine/information retrieval design, information visualization, knowledge management and the social sciences.  That can be eclectic but this is the place for hearing about new work on Wikis, Blogs, Message Boards, and other social media systems like social networking services, micro-blogging systems, and mobile software.

The conference is held this year in May, from the 17th-20th, in San Jose, California.

Here are my pictures from last year’s ICWSM in 2008, held in Seattle, Washington.

There is also a nice picture from Joe McCarthy of Tom Lento and me in front of our poster at ICWSM 2008.

by gumption

Carter Butts delivered a talk about “simple things” that govern the structure of social networks like the limited number of configurations networks can take when the number of nodes is lower than, say, 15.

Phil Bonacich also delivered a keynote address which focused on the role of power in social relationships and the ways that network configurations confer more or less power on particular locations within the network.  People with choices among their interaction partners are able to resist exploitation better than those with few or no choices.

Network researcher Valdis Krebs and Sociologist Barry Wellman attended (that’s me in the middle!).

Sociologist Bernie Hogan from the Oxford Internet Institute and John Kelly from Morningside Analytics were in attendance.

Online Community Business Forum 2009

March 19 – 20, 2009
Sonoma, California – The Online Community Business Forum — where top online executives gather to discuss the intersection of business strategy and online community, in Sonoma, CA.

Mobile Social Media Unconference

23 April 2009
Palo Alto, CA – The Mobile Social Media Unconference is a gathering of strategists, community hosts, device manufacturers, service providers, and content developers to discuss the emerging opportunities and challenges that mobile communities present.

Online Community Unconference 2009

10 June 2009
Computer History Museum, Mountain View, CA – 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.

Online Community Summit 2009

October 8 – 9, 2009
Sonoma, California – The Online Community Summit — where thought leaders in online collaboration gather to discuss best ideas for the future, in Sonoma, California.

2009 Communities and Technologies Conference

C&T 2009
June 25-27, 2009
The Pennsylvania State University
Information Sciences and Technology Building

In an increasingly networked world, the concept of community has taken on new meanings and inspired the development of a wide range of technologies aimed at forging connections, improving communication, and enabling coordination among groups of people. Today, such terms as virtual community, blogging, podcasting, and smart mobs have become commonplace, yet each represents a complex system of hardware, software, and people, shaped by perceptions, norms, rules, and habits, and occurring within varied social and cultural settings.

The Communities and Technologies biennial international conference serves as a forum for stimulating and disseminating research on the complex connections between communities – both physical and virtual – and information and communication technologies. Researchers studying aspects of this interaction between communities and technologies, regardless of disciplinary background, are providing original contributions to the Fourth International Conference on Communities and Technologies.

http://cct2009.ist.psu.edu/workshops.cfm

http://cct2009.ist.psu.edu/program.cfm

I am please to note that a paper about NodeXL will appear at the Communities and Technologies conference, there will also be a workshop on the use of the tool presented prior to the official start of the conference.

Penn State hosts C&T 2009

Hope to see you there!

Here are some pictures from the prior Communities and Technologies conference in 2007 on the campus of Michigan State University in East Lansing, Michigan.

Princeton Center for Information Technology Policy

Princeton’s Center for Information Technology Policy is hosting a conference on “Studying Society in a Digital World”

Thursday - Saturday, April 23-25, 2009 at Princeton University

http://citp.princeton.edu/front/conference-studying-society-in-a-digital-world/

Here are some standout people and talks at the conference:

Lada Adamic, Michigan

Eric Horvitz, Microsoft: 
Through the Lens of a Large Instant-Messaging Network: Planetary-Scale Views on Behavior

Nathan Eagle, MIT: 
Scaling of Sociodynamics

Michael Macy, Cornell

Scott Golder, HP: 
Temporal Rhythms in Electronic Society: Examples from Facebook and Elsewhere

Jukka-Pekka Onnela, Harvard: 
Using Cell Phones to Study the Large-Scale Structure of Social Networks

Paul Resnick, Michigan

Matt Salganik, Princeton:
Community-Generated and Community-Sorted Information

Edward Castronova, Indiana:
The Emergence of Virtual Money: Results from a Virtual World Experiment

Nosh Contractor, Northwestern

Robert Kraut, Carnegie Mellon: 
Theory-Based Design of On-Line Worlds

Jon Kleinberg, Cornell: 
Spatial Signatures of On-Line Behavior

2009 Social Computing Conference

A great conference on social media and related issues will be held this August in Vancouver: 2009 IEEE Social Computing Conference.  I will be reviewing for the conference and will be working on a couple of papers that will be submitted for review.

http://cse.stfx.ca/~socialcom09/

Topics of particular interest for the conference include, but are not limited to:

· Social Computing Theories
· Social System Design and Architectures
· Social Network Analysis and Mining, Semantic web
· Social Behavior Modeling
· Social Intelligence, Social Cognition
· Social Computing Applications such as collaborative filtering, bookmaking, tagging, and multi-agent systems
· Human Machine Interactions
· Emotional Intelligence, Cultural Dynamics, Opinion Representation, Influence Process
· Data Mining, Machine Learning, Information Retrieval, Artificial Intelligence in Social Contexts
· Trust, Privacy, Risk and Security in Social Contexts
· Social Engineering, Tools, and Case Studies
· Services Science, Quality, Architecture, Management, and Tools
IMPORTANT DATES
Workshop Proposal: March 01, 2009
Paper Submission Deadline: April 15, 2009
Authors Notification: June 01, 2009
Final Manuscript Due: June 15, 2009

Professor Ben Shneiderman, from the University of Maryland, Department of Computer Science, will deliver one of the keynote addresses on: “Network Analysis and Visualization for Understanding Social Computing”.

Katy Borner at the Visual Data Analysis Conference in San Jose

It was good to see Katy Borner at the Visual Data Analysis conference held recently in San Jose. Katy is part of the Network Workbench project that provides a comprehensive set of network analysis data sets and tools.

Peter had a big impact on his many students at UCLA and the larger academic community that built on his scholarship.   A lecture from Peter was a great thing that left his audiences feeling both smarter and challenged with a whole new landscape of choices.  Peter brought many people to a better appreciation of the issues of cooperation and conflict, collective action and common goods, of trust and deception in risky transactions.  He made it clear how most of our biggest challenges on this planet are cooperation dilemmas.  He gave many of his students the inspiration to think that conflicts could be resolved and cooperation sustained by leveraging insights from studies of these situations.  His was the only class I ever took that proved mathematically that it paid to be good to other people, even if there were short term costs.  He saw early on the importance of communication networks to change the landscape of cooperation and collective action.  His scholarship extended to the very real world of high tech entrepreneurship- building tools for markets on the Internet.

My thoughts are with his family and friends who appreciate the great presence Peter had.

I am shocked by his loss and will miss him deeply.

UCLA Announcement

Wikipedia Page for Peter

CALL FOR PAPERS

Interact 2009 - Call for papers

INTERACT 2009 – Research and Practice

The twelfth IFIP conference on Human-Computer Interaction
24 – 28 August 2009 in Uppsala, Sweden

Conference website: www.INTERACT2009.org
Paper submission site: https://www.softconf.com/s08/interact2009/

————————————-
CALL FOR PAPERS
————————————-