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

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

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

Click for larger image.

The top most between participants in this graph were:

@timoreilly
@quantifiedself (-1)
@harscoat (-)
@edyson
@qsparis
@egadenne (-4)
@agaricus (-)
@brunoaziza
@adriana872
@chloester

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

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

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

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

I will be speaking at the Jacob T. Schwartz International School for Scientific Research week long Lipari School on Computational Social Science , July 17 – July 23, 2011, Lipari Island, Italy.

This year’s program is dedicated to Computational Social Science: Text and Decisions

Speakers:

• Claudio Cioffi-Revilla: Director of the Center for Social Complexity, Krasnow Institute for Advanced Study, George Mason University, Washington DC.
• Huan Liu: Community Detection and Mining in Social Media [abstract]
  School of Computing, Informatics, and Decision Systems Engineering, Arizona State University
• Roel Popping: Computer-assisted text analysis, and the relevance of decision making and text mining [abstract]
  Department of Sociology, University of Groningen

Tutorials

• Marc A. Smith: Charting Collections of Connections in Social Media: Maps and Measures with NodeXL [abstract]
  Chief Social Scientist, Connected Action Consulting Group
• Calogero Zarba: Introduction to matrix algebra [abstract]
  Neodata Intelligence s.r.l., Italy
• Alessandro Pluchino: Netlogo: An agent based simulation programmable environment [abstract], University of Catania, Italy

As mobile devices become a major method for authoring and consuming social media, location data is increasingly a part of many posts, tweets, check-ins, and messages.  Many Twitter clients, for example, can add the user’s current latitude and longitude to the metadata associated with a tweet.  Other systems like Facebook Places, Google Latitude and Foursquare encourage users to declare  where they are to the world, often passing the information to other social media sites.

Using this location data in network analysis opens up a range of new opportunities.  Instead of a person – to – person social network, location data allows people to be linked to places and, by extension, places can be linked to other places based on the patterns of connection people create when located in a particular place.  A convergence of network analysis and Geographic Information Systems in underway.  A great example of this can be found in this wonderful video from the BBC which demonstrates the idea by mapping the flow of telephone calls, texts, and data around the UK and the wider world.

Link on the BBC

Even better is this video from the SensibleCity group at MIT:

Now, NodeXL (v.156) has the first of a series of features that will start to approximate the experience displayed in the video by supporting the import of location data about networks and plotting networks onto maps.

For now, we have started importing latitude and longitude data that Twitter makes available.  If you check “Add a Tweet column to the Vertices worksheet” in NodeXL, Data, Import, From Twitter Search Network or From Twitter User Network, the Twitter user’s geographical coordinates will be added to the Vertices worksheet when they are available.

Note that not every tweet has a latitude and longitude, in fact many do not (yet).  Further, note that not every latitude and longitude is accurate, many are not.

We need to implement more features for better location data support in a NodeXL workbook, but this is a start.  We are interested in exploring geospatial networks and Twitter is a great data source.  With this data in place we may look into features that emit KML files for exploration in other packages like Google Earth.  A nifty Google Earth/Spreadsheet importer can take small sets (400) of location data points in a spreadsheet and export them to a KML file, something we could implement in the future as well.  In addition we may be able to connect directly with services like Bing Maps and Google Maps to display connections between nodes with known locations.  Metrics that calculate the distance between nodes seem sensible as well.

Location coordinates are the key to a cornucopia of related data about a place.  Given a latitude and longitude it is possible to find the name of the city it is located in, look up data about that location in official records as well as resources like Wikipedia.  Income, education, property values, weather, photos, and more can be pulled together from just a simple lat/long.  All of these attributes could be used to cluster or illustrate the network visualization.

I returned to South Africa to attend the 2010 edition of Mobile Web Africa, a conference focused on the remarkable adoption and development of mobile networks and technology in Africa.

The conference took place on 29th & 30th September 2010 in Johannesburg, South Africa.

I presented a workshop on social media network analysis, see: http://www.mobilewebafrica.com/marc-smith-workshop.php

The conference twitter hashtag #MWA2010 received a significant amount of traffic.  I mapped the collection of collections formed when people who tweeted “#MWA2010″ also followed, replied, or mentioned one another.  The following two EventMaps of the #MWA2010 twitter hashtag illustrates the development of the network.

Map of the connections among people who tweet “MWA2010″ on October 5th, 2010

Map of the connections among people who tweet “MWA2010″ on September 29th, 2010

The later graph is defined by three leading contributors who each generated significant retweeting along with mentions and replies.

I attended the previous 2009 Mobile Web Africa conference in Johannesburg, South Africa, organized by AllAmber Media which also featured a focus on the next wave of mobile devices and services.

Mobile is BIG in Africa.  The “Remote control of the Universe” = Mobile Phone.

The speaker from Samsung last year noted that for many Africans, the mobile device is their first and main method for managing digital objects.  A phone is not just a phone, it is a still and video camera, music player, watch, web browser, flashlight, wallet and file system.

The representative from Yonder Mobile Media noted that mobile phones have now exceeded the installed base of the previously most widely used communication technology: FM Radio.  But mobile is different from FM: mobile devices are two way, provide a method for exchanging payments, and are a primary method of access to the internet for many billions of people.  Mobile is the “first” screen for many people in Africa, not the third screen role that it plays in more developed economies.  Regional services like MXIT and The Grid are offering Internet services tailored to affordable mobile devices.

Photos from this year’s event:

Photos from last year’s event:

Photos from Cape Town:

Mapping mobile social networks with NodeXL: finding key users, groups, and locations

The video is now available:

The video reviews the creation of maps like this:

That illustrate the connections among people who tweet the term “#ecomm2010″, scaled by the number of followers.

Abstract: Social network analysis (SNA) is a powerful method for gaining insight into the massive collections of connections created when many people connect to one another through mobile devices. SNA has been widely applied to desktop social media and is moving into the mobile world. Prominent studies of the “call graph” have been produced at national scales.

Mobile providers are applying SNA to identify key subscribers who can reduce churn and help gain adoption of new services and products. Network analysis has historically had a steep learning curve, but now new tools are making SNA easier for less technical users. This talk will describe social network concepts and their application to mobile data sets. A free and open add-in for the popular Excel 2007 spreadsheet called NodeXL (http://www.codeplex.com/nodexl) can perform many complex SNA tasks like data import, scrubbing, metrics calculation, clustering, and visualization. Applying this tool to call graph and subscriber data sets can reveal key positions in the network that can attract and hold other subscribers in the system.

Examples of network analysis of social media and mobile data sets can be found on the Connected Action blog (http://www.connectedaction.net).

The 2010 Microsoft Research Faculty Summit was held July 12 and 13 in Redmond, Washington.  Among the many panels and discussions related to the state of computer science the NodeXL team had several representatives talking about the ways network science education can be expanded using an easy to use application for network analysis built on Excel.

Jimmy Lin from the University of Maryland also attended to speak about programming in the cloud.

Here is the abstract for the NodeXL talk:

NodeXL – Social Network Analysis in Excel—Natasa Milic Frayling, Microsoft Research; Ben Shneiderman, University of Maryland; Marc Smith, Connected Action

Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft’s NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools—NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theory and information visualization into a simple tool anyone can use. This makes NodeXL of interest not only to end-users but also to researchers and students studying visual and network analytics and their application in the real world. NodeXL has the unique feature that it imports networks from Outlook email, Twitter, flickr, YouTube, WWW, and other sources, plus it offers a rich set of metrics, layouts, and clustering algorithms. This talk will describe NodeXL and our efforts to start the Social Media Research Foundation.

Some photos from the event:

Saul Greenberg

Ben Shneiderman and Andy van Dam

Ben Shneiderman, Natasa Milic-Frayling and Marc Smith

Tom McMail and Marc Smith

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

Peter Pirolli, research at PARC, presented the keynote about the challenges and opportunities for the use of social media to address social problems.

There is growing interest in this space, for example NSF funding was significantly increased this year. For example, there is the new NSF Social-Computational Systems (SoCS) program: http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503406&org=NSF&sel_org=NSF&from=fund

President Obama’s recent speech to the National Academy of Science (http://www.nasonline.org/site/PageServer) sets some of the context for this group’s vision, he speaks about crowd sourcing and its impact on science. (See minute 28:30) video is on the web site of the National Academy of Science http://edg1.vcall.com/video/nas/launch.asp

“I have charged the White House Office of Science and Technology Policy with leading a new effort to ensure that federal policies are based on the best and most unbiased scientific information. I want to be sure that facts are driving scientific decisions – and not the other way around.

As part of this effort, we’ve already launched a website that allows individuals to not only make recommendations to achieve this goal, but to collaborate on those recommendations; it is a small step, but one that is creating a more transparent, participatory and democratic government.”

Elsewhere in the speech there is a refernce to the role of (appropriately) digitizing medical records which I think includes the idea that people will increasingly gather online to work towards better personal health:

“The Recovery Act will support the long overdue step of computerizing America’s medical records, to reduce the duplication, waste, and errors that cost billions of dollars and thousands of lives.

But it’s important to note: these records also hold the potential of offering patients the chance to be more active participants in prevention and treatment. We must maintain patient control over these records and respect their privacy. At the same time, however, we have the opportunity to offer billions and billions of anonymous data points to medical researchers who may find in this information evidence that can help us better understand disease.”

There seems to be a role for the kinds of online communities and social media that people turn to when facing physical or medical challenges.

National Initiative for Social Participation at University of Maryland
http://iparticipate.wikispaces.com/Motivating+Scenario
http://chronicle.com/daily/2009/05/17280n.htm
http://www.flickr.com/photos/marc_smith/sets/72157617551332795/

Princeton Center for Information Technology Policy

Here is the slide deck I presented at 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 posted to flickr.  Here is the slide deck I presented along with my talk at the conference.

The theme of mobile sensor data shared via social networks was one reinforced by the many presentations at the conference. 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.

Held in conjunction with SocialCom ’09
29th-30th August, Vancouver, Canada
http://thesocialmobileweb.org

The mobile space is evolving at an astonishing rate. At present there are over 3.5 billion mobile subscribers worldwide and with continued advances in devices, services and billing models, the mobile web looks set to inspire a new age of anytime, anywhere information access. The inherent characteristics of mobile phones enable new types of interactions, e.g. mobile phones are personal to the individual, they are always on and always connected. And as such we are seeing a shift towards mobile devices for social mediated tasks. The world is also witnessing an explosion in social web services. Online social networking sites such as Facebook and MySpace continue to experience huge increases in usage, with more and more users seeking novel ways of interacting with their friends and family.

In this workshop we are interested in the combination of these two exciting research spaces: the social web and the mobile space. We believe that the social mobile web is going to be a highly influential research area in the near future. As such this workshop will investigate the current state of the social mobile web. Topics of interest to this workshop include (but are not limited to) the following:

* Novel social interactions on mobile devices.
* Social mobile content sharing and distribution services.
* Context aware mobile services – beyond location based services.
* Social mobile search and social mobile browsing.
* User evaluations of social mobile services.
* Mobile user interfaces that incorporate social elements.
* Mobility and social networks.
* Models of mobile social behavior and mobile traces.
* Urban gaming, mobile mixed reality, etc.
* Innovative social mobile applications.

This workshop is targeted towards researchers working within the mobile web and social web spaces.  Participants are invited to submit: (1) a short position or demonstration paper of 2-4 pages in length or (2) a full length technical paper of up to 10 pages in length. Papers should be in IEEE publication format and should be submitted as a PDF file via email to organizers@thesocialmobileweb.org. Workshop papers will be published by IEEE CS Press. Note that at least one author of accepted papers needs to register and attend the workshop.

Organising Committee
————————–
* Karen Church, Telefonica Research, Barcelona
* Josep M. Pujol, Telefonica Research, Barcelona
* Barry Smyth, University College Dublin, Ireland
* Noshir Contractor, Northwestern University, Evanston

Program Committee
————————–
* Lada Adamic, University of Michigan
* Alex Arenas, Universitat Rovira i Virgili
* John Breslin, DERI Institute, NUI Galway
* Meeyoung Cha, Max Planck Institute for Software Systems
* Augustin Chaintreau, Thomson Research
* Nathan Eagle, MIT/Santa Fe Institute
* Andreas Flache, University of Groningen
* Jill Freyne, CSIRO
* Scott A. Golder, Cornell University
* Carmen Guerrero, Universidad Carlos III
* Tom Heath, Talis
* Matt Jones, FIT Lab, Swansea University
* David Lazer, Harvard University
* Nuria Oliver, Telefonica Research
* Alex Payne, Twitter
* Ramon Sang¸esa, Technical University of Catalonia, Citilab
* Albrecht Schmidt, University Duisburg-Essen
* Marc Smith, Telligent Systems
* Roger M. Whitaker, University of Cardiff
* Peter Mika, Yahoo Research Labs

Important Dates
11th May 2009: Deadline for submissions
5th June 2009: Notification to authors
15th June 2009: Final paper version deadline
29th-31st August 2009: Conference dates

Website
Further details are available from the workshop website at: http://thesocialmobileweb.org

My colleague Prof. Ben Shniederman is positively impressed by these images.  He writes, “Notice how the node layout remains stable as edges are removed, so by the 4th figure the edges can all be followed easily….”.  This is one of the themes he highlights in his paper and presentations about problems and improvements in network graph drawing (see: http://www.cs.umd.edu/hcil/nvss/and in particular http://www.cs.umd.edu/hcil/pubs/presentations/NVSS-3.ppt). Prof. Shniederman’s  5th edition of Designing the User Interface is now available with two full chapters on the website with wordles to open each chapter.

A somewhat related article ran the same day in the Style section on The Celebrity Twitter Ecosystem (http://www.nytimes.com/2009/03/29/fashion/29twitter.html). This image focused on the linkages between well known people using Twitter and, by extension, revealing who they follow and who follows them in the social network.

In the first image no names are associated with the nodes, in the second the names are the major point of the diagram.

The practice of “anonymization” of network graphs may be moot in light of a recent publication mentioned on the Social Network Analysis email list (SOCNET) by Mark Round from QinetiQ of a paper:

De-anonymizing Social Networks – Arvind Narayanan & Vitaly Shmatikov
(http://33bits.org/2009/03/19/de-anonymizing-social-networks/)

which suggests that just publishing the unique pattern of links around an individual is sufficient to identify them in an otherwise anonymized data base.

Abstract:
Operators of online social networks are increasingly sharing
potentially sensitive information about users and their relationships
with advertisers, application developers, and data-mining researchers.
Privacy is typically protected by anonymization, i.e., removing names,
addresses, etc.
We present a framework for analyzing privacy and anonymity in social
networks and develop a new re-identification algorithm targeting
anonymized social-network graphs. To demonstrate its effectiveness on
real-world networks, we show that a third of the users who can be
verified to have accounts on both Twitter, a popular microblogging
service, and Flickr, an online photo-sharing site, can be re-identified
in the anonymous Twitter graph with only a 12% error rate.
Our de-anonymization algorithm is based
purely on the network topology, does not require creation of a large
number of dummy “sybil” nodes, is robust to noise and all existing
defenses, and works even when the overlap between the target network
and the adversary’s auxiliary information is small.

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

Program on Networked Governance CCCSN Seminar 2009-03-02: Tanzeem Choudhury from Networked Governance.

This is a very informative lecture at Harvard from Tanzeem describing her Dartmouth group’s work to create, deploy and interpret the data from mobile inter-personal sensors.

Hyperlinked Society

In my paper From Hyperlinks to Hyperties in  The Hyperlinked Society: Questioning Connections in the Digital Age (Joseph Turow and Lokman Tsui, Editors; which came from the symposium of the same name at Annenberg School of Communication in Philadelphia).  I propose one of the ways mobile devices and social software will change the nature of the “interaction order” is to create “hyperties” – here is the abstract of the paper:

Goffman did write about telephone conversations as well as the ways broadcasters altered the patterns of spoken interactions in radio transmissions but he died before mobile phones became popular or online Internet social spaces became mainstream.  Several scholars have applied Goffman to social interaction in cyberspace.  There are lots of possible connections: Goffman wrote at length about the ways people “present” their identities to one another as if we were all actors on a stage.  After decades of “reality TV” this is not the revolutionary thought it once was in Goffman’s day.  Today his work can be a guide to studying the ways people now use the Internet to create representations of themselves and interact with one another.  Profiles on social network systems and other kinds of Internet based media publication tools are a new kind of surface for displaying membership insignia and symbols of connections with other people.  Like clothing or landscaping, Internet media are a medium for self-expression and claims to membership in a number of demographics and sub-cultures.

It is no longer necessary to bring Goffman to the Internet; the Internet is coming to Goffman.  Goffman’s work has even more value in the coming years.  The main focus of his work was the minute details of face-to-face interactions.  Goffman relished the details of careful control of eye contact and posture, tone of voice and timing.  When applied to “online” media this aspect of Goffman’s work has been applied metaphorically to the interactions of avatars and user names.  It is certainly possible to extend Goffman into these Internet spaces.  But now Internet spaces are extending themselves into the Interaction Order.

Mobile Internet devices are now along for the ride in many of the situations Goffman wrote about: meetings and encounters between people which feature exchanges and evaluations of identity claims.  Mobile phones are becoming more general purpose networked mobile computers.  Today these devices remain end points of Internet data more than sources.  But increasingly mobile devices have sensors that allow them to measure physical states of their owners and the presence of others in proximity.  When my phone notices your phone and can tell that it is your phone new opportunities emerge for people interacting in the interaction order.

The “interaction order” has been very analog and few innovations have taken place there — with a few notable exceptions.  Speech and body adornment were both big innovations that gave humans a big advantage in the creation of complex societies.  Since those novel practices there have been few things that have dramatically altered the basic nature of human to human interaction in face-to-face situations.  It could be argued that refinements like amphitheaters increase the number of people who can usefully gather in one place and still hear one another.  Similarly, writing and printing altered the interaction order only to the extent that sitting side-by-side with someone looking at the same relatively rare books created a structured interaction space but not new ways of presenting who we are or reading one another’s claims.

Clocks and maps help people get to an interaction at the right time and in the right place, but they do not change the basic capacity to signal between people.  Phones and cell phones create new kinds of spaces for an interaction order – with novel rules, but they do not change face-to-face interaction as much as they pull people out of face-to-face interactions and into a network mediated interactions.

Goffman will have renewed value for those trying to understand the impact of mobile devices because for the first time networked digital machines are aware of social interactions and are able to alter how we interact with each other.  The Interaction Order is “electrified” when we bring devices into our interactions with other people and those devices help us display the right symbols to others and access the right symbols about others.

After a lovely dinner you order a third glass of wine, take a sip and your mobile phone rings.

Its your health insurance company’s computer. You take the call.

“We’re delighted to see you are enjoying yourself this evening!” the cheerful voice synthesis exclaims.

“Please note, however, that you are now at the policy limit for blood alcohol level. To purchase a 24 hour waiver that will allow you to exceed this limit, press 1. A fee of $20 will be charged to your monthly co-payment invoice. To decline waiver coverage, press 2. Please note that if you decline coverage your blood alcohol level must drop under the policy limit within 45 minutes. Continued elevated blood alcohol above your policy limit will constitute breach of your coverage agreement and you may loose all coverage for alcohol related illnesses including injuries received from accidents that may be caused by impairment.”

With a paid-for glass of wine on the table, many people may just go along with the offer (their judgment may already be somewhat impaired).

Real-time health monitoring is an application that is rapidly developing.  Our mobile devices are likely to play a central role in enabling a wide scale real-time continuous monitoring of health related data.  The Quantified Self meet-up is exploring many aspects of this space, but discussion of ways large institutions could use this data has not been a large focus so far.

Medical compliance is a huge issue: most of us do not take prescribed medicines the way we are “supposed to” – skipping doses, doubling up, or quitting a series of medications once symptoms subside.  A real-time assessment of our blood (among other measures) would go a long way to reducing the costs of illness and treatment.  In a world of scarce medical resources, can competitive societies allow their members to be slothful and subsequentially expensive to maintain?

The Intel Health Guide is a good example of this emerging trend, although still in a “desktop” form factor.

Intel Health Guide Device

Other examples can be found in the iPhones app store where health and navigation and travel categories of applications are starting to collide.

The next meeting of the “Quantified Self” group will be held on January 27th, 2009 at the University of California, Berkeley School of Information.

The group focuses on the emerging practice of recording lots of data about your physical state and activity.  Its where life logging meets populations of people grappling with illness or seeking optimal health.  The idea is that close records of our health will reveal connections between behaviors and outcomes, letting us change our behavior or at least detect early when things go wrong.  Others are just interested in detailed record keeping, an extension of detailed blogging or life streaming.  In many cases people are sharing these records with others, sometimes to get social support to meet a goal like running more miles or loosing more pounds.

I find the topic interesting for all these reasons and because the technologies for the “Quantified Self” are also going to be applied to the “Quantified Other” – sensors that record data about your body may ultimately notice that you are near other people.  It is when machines automatically notice when people are near people that I think the “QS” effort will have greatest impact.

Kevin Kelly has been blogging about “QS” on a blog of the same name. This will be the 3rd meeting of Quantified Self people.  I was able to attend the second meeting at the IDEO offices in San Francisco which had a great turn out of people and presentations of projects for assembling personal biographies and recording fleeting thoughts.  Hope to see you at the next meeting!

These projects point towards a world in which computers and mobile devices do more than connect us to the network, they will sense the world around us and reason about both our location and who is with us.  Combined with back-end data mining, new mobile sensor studded devices are coming that will alter the nature of social interaction in its last, most analog hold out: face-to-face, co-present interaction.

I want to explore this change in the nature of what the sociologist Erving Goffman referred to as the “interaction order“.  We are living through the early stages of the “electrification of the interaction order”, a time in which the ways we interact with one another is changed dramatically by the availability of mobile social information networks.  Online social networking, content sharing and discussion systems have effects that are multiplied when channeled through a device carried by every person and active in every interaction, however fleeting.  

Imagine going to a business meeting or conference and having Facebook suggest that you link to the people you spent the longest time talking to.  Mobile social computing will add more content to the torrent already generated by “desktop” experiences.  Some projects are already digging into this area: good examples include companies and products like nTag.com, SpotMe.Com, and the many trail and path tracking applications now appearing in the iPhone AppStore.  Scott Counts and I wrote about a location based social networking application that demonstrated many of these features as well as search and matching features that have yet to appear in the first wave of production systems.

A first step in this direction is to focus more on the analytic back-ends that will be needed for the management of all forms of social media repositories.  Community analysis servers that provide a dashboard of community health and activity indicators will be a critical differentiating feature for community hosts, managers, and leading participants.  Successful communities will be those that can cultivate contribution the best while managing conflict at the lowest cost.  Once desktop bound social encounters are channeled through an analytics console more real-world events sensed by mobile devices can be added to the mix.  

I am looking forward to some time to push back and reflect more about these changes while looking around for new ways to explore them.  I will take some time to get my family settled into our new home in California.  I hope to catch up with many people!  I will also be visiting Yale, University of Maryland and Berkely for talks this fall.  I plan to attend the Microsoft Research Social Computing Symposium in Redmond (it will be good to be back!) and the Conference on Information and Knowledge Management (CIKM) in Sonoma.

My old masmith@microsoft.com email address is no longer active, so please contact me at marc.smith.email at gmail.com.  

I look forward to staying in touch with my many friends and colleagues at Microsoft while finding the time now to meet with a wide range of people interested in social media.