The NodeXL team from the Social Media Research Foundation has released a web application that allows users to upload network files and download files other users have uploaded.

The Social Media Research Foundation is dedicated to Open Tools, Open Data, and Open Scholarship.

The NodeXL Graph Gallery on the Web enables the research community to collectively gather and share data sets.

Users of NodeXL will notice a new NodeXL>Data>Export>To Web Gallery menu option which opens this dialog box:

Users will be able to browse the NodeXL Web Gallery for graphs that were recently uploaded:

Users will be able to search for graphs that contain certain keywords:

Users can then get details about the network graph and download those files they would like to investigate.

Bits exist along a gradient from private to public.  But in practice they only move in one direction.

Thus, there are two destinies for information: public or oblivion.

Information wants to be copied.

This is not the same as information wanting to be free (or expensive), or information wanting *you* to be free.  Information probably prefers to be free because it may increase the rate at which it is copied, not because it is inherently liberating to the user.  In fact, the “free” quality of some information is probably not liberating at all.  Copying and liberty are orthogonal.

Information diffuses over time: access rights to information can expand over time, but only rarely (ever?) does data become less available, and once available publicly, information is almost never entirely private again.

With enough copies on enough devices, information becomes essentially public. The state of being public may come in degrees, some things are more public than others.  Much information is public in principle but enjoys security by obscurity. Obscurity is eroded by increasing availability of computing resources that make collection and machine analysis affordable at large scales.  The banality of data is no protection.  “No one cares what I think/do/say/click” is not a valid assumption.  In aggregate the banal is data and fuel to many business models.  Maybe no one *cares* what you tweet, click, buy or search for, but many businesses make it their business to aggregate these scattered faint signals and build detailed profiles to drive commerce and customized views of data.

Some information is destroyed, never to be recovered.  This is the only way information can avoid eventually (potentially) becoming public. But less and less data now meets this fate.  Delete is a declining feature of many systems.

Information that is not public and has not yet been destroyed is just waiting to change to either state.

Despite security systems, many private bits are eventually exposed by people passing material to someone else who then accidentally makes them public, or they do so unintentionally themselves by leaving files in publicly accessible locations that are visited by search engine spiders and other web crawlers.  Even professionally managed private data repositories are subject to subsequent distribution, infiltration or error. Data spills are becoming more common. Billions of records are hemorrhaged  into the public regularly.  If well funded organizations cannot secure their information, the rest of us should take note.

It may not be possible for big organizations or any organization to secure their networks, or even do so sufficiently effectively to give users a practical period of privacy, however short.  Eventually private bits, even when encrypted (no matter how well), become public because the march of computing power makes their encryption increasingly trivial to break and their exchange over networks (no mater how well secured) is subject to leaking, intentional and otherwise.  Private bits may only have a “half-life” during which they retain their non-public existence.  The length of this half-life may itself be getting shorter.   Mary Branscome suggests that there could be a physical law in operation: the natural entropy of access control lists?

All bits that persist are destined to be public, and once public never to be private again. Unless they are destroyed.

I argue that the only bits that you cannot find are the ones you need right now. The only bits you cannot get rid of are the ones that are most embarrassing to you right now.  Just because you cannot find the bits you want does not mean that no one else can find those bits.

All your bits are belong to us.

This issue is getting more important as we are invited to use systems that promise selective sharing of data and other tools generate ever more data to potentially share.  Anything that puts your bits into the cloud promises selective sharing.  I believe and hope my much beloved Dropbox account is separate from all the others, except for the one’s I chose to share with. And I think it is, expect for that glitch they had, the details of which elude me (but I think we’re good now, and I so depend on Dropbox I do not know what I would do without it). But all these walls are just made out of a few lines of business logic and an Access Control List. ACLs rule our access to digital objects with an iron fist until they don’t for the many human and technical reasons mentioned.  Like most human infrastructures these selective sharing mechanisms are subject to failure and attack.

Now new sources of data captured from the details of everyday life by sensors and  services are increasingly recorded by external systems and by people themselves, generating new streams 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 can map their internal social network structure as an accidental by-product of their communication practices.  Studying these data sets is a focus of growing interest.  Research projects like SenseCam are now becoming products and existing services like MingleSticks, Poken, FourSquare, and Google Latitude already deliver many of these features. Devices like iPhone and Android phones are weaving location information into every application.

Some steps are still in progress: when my phone notices your phone a new set of mobile social software applications become possible as whole populations capture data about other people as they beacon their identities to one another. Additional sensors will collect ever more medical data with the intent of improving our health and safety, as early adopters in the “Quantified Self” movement make clear.

But the  consequences of data diffusion are becoming difficult to predict.  Social media systems are being linked to one another to enable cascades of events to be triggered from a single message as status updates are passed among Facebook, LinkedIn, Twitter, and blogs.  Tools now 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.

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.  More exploitative applications are also likely.

The result will be lives that are more publicly displayed than ever before.  The collapse of roles (“lowest common denominator culture”) described by Bernie Hogan (listen starting in about 40 minutes – but the entire talk is good and worth a listen) as described by the sociologist Erving Goffman may be one consequence: we are interacting with everyone when we interact with anyone.  Secret shared meanings may still be possible — but selectively shared bits are not, at least not very reliably so in the short term and almost certainly not in the medium term.

Therefore, all services that promote the idea of “selective sharing” are selling a myth.  The more you trust that information you generate can be contained, the more potential there is for an “explosive decompression” as data intended for an individual or a small group becomes suddenly available to a large group or a complete population. Private bits are in a state of high potential energy, always poised to become public.

Engineering is the science, art and practice of containing and directing  forces. Information system engineers might be up to the challenge of delivering selective sharing.  And when combined with law, regulation and social practices, technology could make selective sharing real the way that engineers manage the flow of powerful but dangerous flows of high pressure steam through power plants.  However, recently even high pressure steam engineers working with nuclear fuels have faced some very bad failure conditions beyond their predicted scope.  Information technologists may face analogous issues when managing high pressure containers of selectively shared information.

My policy is not to give up all forms of privacy, I still keep my email and other data behind passwords that I do not (knowingly) share.  I share lots of pictures on flickr but not all of them are public.  I would prefer to keep lots of financial, medical, and personal stuff selectively shared.  I’d like these features to work.

But I have started to understand that my data is likely to be open to others, if not now then some day — and probably sooner than I expect. The net/cloud  holds a good sized and growing  chunk of my digital life and I would like selective sharing features (if I could handle the cognitive tax of managing them).  I just do not believe it is a reasonable expectation.  In a world of increasing interconnection and unifying name and search spaces, data may not be something you can keep local for long.

Tools that suggest that we can reliably segregate content and limit its diffusion are suggesting that water does not roll down hill.  Those who believe that are likely to get wet.

With the VOSON Data Provider Plugin for NodeXL, you can now access VOSON hyperlink network construction services from within NodeXL, an Excel 2007/2010 template for analyzing social media network data. So there are two ways you can use VOSON for analyzing hyperlink networks: (1) via the VOSON System (which you login to using a web browser); (2) via VOSON+NodeXL. The VOSON System is a special tool for hyperlink network construction and analysis. NodeXL provides access to various types of social media network data sources, e.g. Facebook, Twitter and, now, WWW hyperlink networks via VOSON.

Developers interested in creating their own data import “spigots” for NodeXL may be interested in this post on the NodeXL Codeplex discussion board: For Programmers: About NodeXL Plug-Ins.

To get access to the VOSON+NodeXL plugin and documentation you first need to register for a VOSON user account.

NodeXL has a number of data importers that can create a network of connections from social media data sources like Twitter, YouTube, flickr, email, and the WWW (along with a number of other data import formats like GraphML, UCINet, CSV, and other Excel workbooks with data).

To create a network you just select the search terms and configurations you want from the NodeXL>Data>Import menu.

If you want to create the same network every day (or at any schedule), a recent feature (since version .125) of NodeXL can help. NodeXLNetworkServer.exe is an application that ships with NodeXL along with a sample configuration file called SampleNetworkConfiguration.xml. By editing the configuration file you can set NodeXL to collect anything available in the menu through Excel.  So far we have exposed the two Twitter data collectors (more on the way) so the configuration file asks you to select a search term or a user’s name, the size of the network and the details you want reported along with the location and name of the destination file that NodeXL will create.  Answer these questions by editing the config file and save it with a useful name that includes the search term.

Step by step details after the jump:

Editing the Configuration file

NodeXL ships with a SampleConfigurationFile.xml that you should copy, rename and edit.

You may want to create a directory to hold this configuration file if you expect that there will be many files.

The configuration file is written in XML but it it is very human readable and editable.  Here are the key elements of the file that depend on you to choose and configure the file appropriately.

NetworkType Specifies the type of network to get.  Must be one of the following values: TwitterSearch or TwitterUser

After setting NetworkType, you must also edit one of the following sections:

TwitterSearchNetworkConfiguration

TwitterUserNetworkConfiguration

TwitterSearchNetworkConfiguration is used only if NetworkType is TwitterSearch.

SearchTerm - What to search for.

WhatToInclude - What to include in the network.  This must be a combination of the following values, separated by commas:

Statuses - Include each person’s status (tweet).

Statistics - Include each person’s statistics.

FollowedEdges - Include an edge for each followed relationship.

RepliesToEdges - Include an edge from person A to person B if person A’s tweet is a reply to person B.

MentionsEdges - Include an edge from person A to person B if person A’s tweet mentions person B.

<WhatToInclude>Statuses,Statistics,FollowedEdges,RepliesToEdges,MentionsEdges</WhatToInclude>

MaximumPeoplePerRequest - The maximum number of people to request for each query, or leave empty for no limit.

NetworkFileFolder - Full path to the folder where the network files should be stored.

NetworkFileFormats - Specifies the file formats to save the network to.  This must be a combination of the following values, separated by commas:

GraphML - Save the network to a GraphML file, which can be imported into a NodeXL workbook.

NodeXLWorkbook - Save the network directly to a NodeXL workbook.  To use this option, the NodeXL Excel Template must be installed on this computer.

<NetworkFileFormats>GraphML,NodeXLWorkbook</NetworkFileFormats>

AutomateNodeXLWorkbook - Specifies whether the NodeXL Excel Template’s automate feature should be run on the workbook.  Must be true or false.  This is used only if NetworkFileFormats (above) includes NodeXLWorkbook.

If true, the automate options you most recently set in the NodeXL Excel Template are used to automate the workbook.  To set the automate options, do the following:

1. Open the NodeXL Excel Template.

2. In the Excel ribbon, Go to NodeXL, Graph, Automate.

Note that the “On this workbook” and “On every NodeXL workbook in this folder” selection in the Automate dialog box is ignored when automating the workbook from the NodeXL Network Server.

<AutomateNodeXLWorkbook>true</AutomateNodeXLWorkbook>

TwitterUserNetworkConfiguration

This section is used only if NetworkType is TwitterUser.

ScreenNameToAnalyze - The screen name of the Twitter user whose network should be analyzed.

WhatToInclude - What to include in the network.  This must be a combination of the following values, separated by commas:

FollowedVertices – Include a vertex for each person followed by the user.

FollowerVertices - Include a vertex for each person following the user.

LatestStatuses - Include each person’s latest status (tweet).

FollowedFollowerEdges - Include an edge for each followed relationship if FollowedVertices is specified, and include an edge for each follower relationship if FollowerVertices is specified,

RepliesToEdges - Include an edge from person A to person B if person A’s latest tweet is a reply to person B.

MentionsEdges - Include an edge from person A to person B if person A’s latest tweet mentions person B.

<WhatToInclude>FollowedVertices,FollowerVertices,LatestStatuses,FollowedFollowerEdges,RepliesToEdges,MentionsEdges</WhatToInclude>

NetworkLevel - Network level to include.  Must be One, OnePointFive, or Two.

MaximumPeoplePerRequest - The maximum number of people to request for each query, or leave empty for no limit.

NetworkFileFolder - Full path to the folder where the network files should be stored.

NetworkFileFormats -Specifies the file formats to save the network to.  This must be a combination of the following values, separated by commas:

GraphML -Save the network to a GraphML file, which can be imported into a NodeXL workbook.

NodeXLWorkbook - Save the network directly to a NodeXL workbook.  To use this option, the NodeXL Excel Template must be installed on this computer.

AutomateNodeXLWorkbook

Specifies whether the NodeXL Excel Template’s automate feature should be run on the workbook.  Must be true or false.  This is used only if NetworkFileFormats (above) includes NodeXLWorkbook. If true, the automate options you most recently set in the NodeXL Excel Template are used to automate the workbook.  To set the automate options, do the following:

1. Open the NodeXL Excel Template.

2. In the Excel ribbon, Go to NodeXL, Graph, Automate.

Note that the “On this workbook” and “On every NodeXL workbook in this folder” selection in the Automate dialog box is ignored when automating the workbook from the NodeXL Network Server.

One key configuration is this last choice to turn on the automated processing of the resulting data set.  If you set this to true, NodeXL constructs a Twitter social network and then performs all of the steps of automation that you define.  For example, NodeXL can calculate graph metrics, find clusters, create subgraphs, map a set of autofill column mappings of data to display attributes, set graph layouts and settings and render a graph without any human intervention.

Once you have a properly edited configuration file you can simply open a command line session (go to the Start menu, type in “CMD”) and type the following:

> NodeXLNetworkServer.exe SampleNetworkConfiguration.xml

And you will get a stream of messages about what parts of the network are being actively collected:

This is a simple example and not too useful: you may as well just do this through the NodeXL Excel interface.  But things get more interesting when one more piece is added: Windows Task Scheduler.  You may not see it that often but Task Scheduler is on almost every Windows desktop and can be used to automate the collection of NodeXL data sets from Twitter and other sources of social media networks.

To get to Task Scheduler just type its name into the Start Menu search box.  It should look like this:

Using this tool you can create new Tasks that will execute on a specific time and frequency.

Create and select a new folder (call it something like “NodeXL Data Collections”) under Task Scheduler Library to hold all your NodeXL data collections separate from other scheduled tasks.

Use the Create Task menu item on the far right.

You will get a Create a task dialog box:

Enter a Name and a Description that captures the search terms of your query and then select the “Actions” tab.

Actions are where the command that you want to execute is defined.  Select “New…” to create a new Action.

This will open a dialog box in which you can define the program to be run along with any settings.

Enter the complete path to the NodeXLNetworkServer.exe application in the “Program/script” field.

Add the complete path to the configuration file in the “Add arguments” field.

To easily capture the complete path (and the quotation marks needed if there are spaces in the path) hold the SHIFT key down while right clicking the name of the configuration file you want to schedule for collection.  You should see an option “Copy as Path” which will place the needed information into the clipboard.  After selecting “Copy as Path”, return to the “New Action” dialog box and paste the path into the “Add arguments” field.

Once the path to the NodeXLNetworkServer.exe file and the path to the configuration file have been entered into the New Action dialog, shift to the Triggers tab of the Create Task dialog.  Select “New…” to create a new trigger.

Triggers are defined by many things, but we will focus on time.  When the New Trigger dialog is set to “On a schedule” you can choose the time and frequency to run the collection.  If you want to run a collection daily at 7:01:30AM each day the following settings should work:

Once the time and recurrence are set select OK and you have a new task!  You may want to create a task that starts in a minute or two to test that the event fires properly.  You can then schedule these collections to run at an hour when you will not be bothered by the interruption.  Multiple collections can be scheduled but several limits suggest that only a few can run simultaneously.  You may want to start collections only a few times a day or hour to allow one collection to complete before others begin.  When these tasks do execute you should see a collection session appear in a console window and report updates as it steps through the many stages of constructing a network dataset.

Collection is much faster if you have a rate limit lifted account, which you must request from Twitter.  With a credentialed rate-limit lifted account you can perform several queries per hour.  With a regular account with credentials (your Twitter login) you can get one or two queries per day depending on the size of the data collected.  In either case it is possible to reach the limit that Twitter will provide.  When that happens NodeXL will pause the collection and wait until the API query budget refreshes and Twitter is willing to serve more query results.  As a result, even accounts without rate-limits lifting can create large complex social media network maps, although at a much slower rate.

http://www.cs.umd.edu/hcil/soh/

The HCIL Government Applications of Social Media Networks &
Communities Workshop, as part of the 27th Annual Human Computer Interaction Lab (HCIL) Symposium, at the University of Maryland, examined how social media can be systematically applied to increase civic participation on national priorities.

When: Friday, May 28, 2010, 9:30am-4:00pm
Where: CSIC Building, UMD, College Park
Who: Government thought leaders, system developers, and agencies; industry partners, researchers, and students

Photo by Ben Shneiderman

Front row (left to right): Brad Hesse, Betsy Rebert, Claudia Louis,
Vladimir Barash, Derek Hansen, Robin Naughton.
Middle row: Scot Golder, Rex Robison, Yan Qu, Joe Pringle, Natasa
Milic-Frayling, Amanda Shanor, Leonard Lidov, Laura Milner
Back row: Robert Altiero, Mark Edson, Keith Walker, Tim Clausner, Marc
Smith, Nick Violi, Brian Dennis, Manuel Freire, John Bertot, Derrick
Cogburn, Jennifer Preece, Francy Stilwell

Not pictured: Ben Shneiderman

The Friday, May 28th all day event focused on the use of social media data in improving the quality of government.

May 28th, 2010: Government Applications of Social Media Networks and Communities
Derek Hansen, Marc Smith, Jenny Preece, Ben Shneiderman
Federal, state, and local governments are discovering interesting and ambitious ways that social media can be used to increase civic participation in decision-making, health-care /wellness, energy sustainability, education, disaster response, community safety, scientific research, etc. This workshop will invite attendees to present current projects, design strategies, evaluation methods, and analytic tools. Issues such as universal accessibility & usability, privacy protection, and reliability will be discussed.

Attendees …
• discussed interesting and ambitious ways that federal, state, and local governments are using social media in decision-making,healthcare/wellness, energy sustainability, education, disaster response, community safety, scientific research, etc.

• explored how analytic tools like NodeXL (http://nodexl.codeplex.com/) can help systematically analyze social media initiatives and mine social media sites for useful information.

• identified the unique challenges of using social technologies in a government context and design strategies and policies that help overcome those challenges

Participants included:
• Vladimir Barash, Doctoral student, Information Science, Cornell University
• John Bertot, Professor, iSchool, UMD
• Derek Hansen – Assistant Professor, iSchool, UMD and director of Center for the Advanced Study of Communities and Information (CASCI)
• Scott Golder, Doctoral student, Sociology, Cornell University
• Bradford Hesse, Chief of the National Cancer Institute’s Health Communication and Informatics Research Branch (HCIRB)
• Natasa Milic-Frayling, Principal Researcher, Microsoft Research Cambridge
• Cynthia Parr, Director, Special Pages Group, Encyclopedia of Life, Smithsonian
• Jenny Preece – Dean, iSchool, UMD.
• Ben Shneiderman – Professor, Department of Computer Science, UMD, and founder of the Human Computer Interaction Lab (HCIL).
• Marc Smith – Chief Social Scientist, Connected Action Consulting Group, director of the Social Media Research Foundation

Slides available from:

http://www.cs.umd.edu/hcil/soh/workshop_hansen.shtml

Schedule

8:30 – 9:30am: registration and continental breakfast

9:30am: Introductions

10:00am: “Technology-Mediated Social Participation: Promoting a Research Agenda” Ben Shneiderman & Jenny Preece, University of Maryland

10:30am: “Enabling Citizen Mapping of Government Networks with NodeXL” – Marc Smith & Derek Hansen, Connected Action and University of Maryland

10:50am: Break

11:00am: “Open Government, Social Media, and Information Policy: Constraints and Barriers” – John Bertot, University of Maryland

11:20am: “New Approaches to Collecting Public Input Online” – Joe Pringle, Forum One Communications

11:40am: “Visualizing Social Data to Improve Diplomacy” – Leonard Lidov, Morningside Analytics

12:00 – 1:00pm: lunch

1:00pm: “Using New Media for Citizen Engagement: Experiences from the General Services Administration” – Leilani Martinez, Center for New Media & Citizen Engagement, U.S. General Services Administration (GSA)

1:30pm: “Supporting Lifelong Learning & Institutional Transformation with New Media” – Michael Edson, Web and New Media Strategy, Smithsonian Institution

1:50pm: “Says who? Legitimacy in Online Collective Action: Enthusiasts and Interest Groups in Wiki Government” – Scott Golder & Vladimir Barash, Cornell University

2:10pm: “From Research of Social Media to Socially Mediated Research” – Natasa Milic-Frayling, Microsoft Research, Cambridge UK

2:30pm: Break

3:00pm: “Health 2.0: Putting the Power of Open Science to the Task of Improving the Nation’s Health” – Bradford Hesse, Health Comm & Informatics Research Branch, National Cancer Institute

3:20pm: Wrap-up discussion

4:00pm: Depart

Technology-Mediated Social Participation: Promoting a Research Agenda

Jenny Preece and Ben Shneiderman, University of Maryland

With support from the National Science Foundation, we have run two research agenda-setting workshops that clarify how social media can address national priorities.  The first, in Palo Alto, CA engaged companies and the second in the Washington, DC area reached out to government agencies.  Our report will describe the national priorities that can be addressed, deep science theories, technology challenges, and scope of educational changes needed in K-12, universities, professional training, and citizen awareness.

Enabling Citizen Mapping of Government Networks with NodeXL

Marc Smith & Derek Hansen, Connected Action Consulting Group and University of Maryland

Social network analysis can serve as a powerful analysis and visualization method to understand connections between people and institutions. Until recently, only those with advanced degrees and technical know-how have been able to perform social network analysis. We will introduce NodeXL, a plugin for Excel 2007, that allows non-technical experts perform social network analysis, particularly of social media networks of interest. We will discuss applications of NodeXL to government data and social media initiatives.

Open Government, Social Media, and Information Policy: Constraints and Barriers

John Bertot, University of Maryland

Much movement and discussion surrounds the use of social media technologies by the federal government in order to create a more open, transparent, and participatory government.  Since the inauguration of the Obama Administration, government agencies have been required to engage in open dialogs, create open government plans, and otherwise use a range of social media technologies.  But these efforts belie an antiquated and contradictory information policy environment that hampers innovation and use of a range of participatory technologies by government agencies such as twitter, facebook, and YouTube.  Though agencies currently are using these technologies, there are a number of policies (e.g., laws, memos, administrative code) that prevent agencies from truly engaging in innovative uses and practices through social media technologies.  This presentation identifies selected policy conflicts and considerations that need resolution for federal government agencies to be able to successfully engage the use of participatory technologies.

New Approaches to Collecting Public Input Online

Joe Pringle, Forum One Communications

Federal government agencies are experimenting with social media, crowdsourcing, and other collaborative approaches to soliciting, collecting, and responding to public input.  This includes everything from formal rulemaking comment collection to ideascale events to online brainstorms such as USAID’s recent Global Pulse event.  Chris will highlight common online approaches to using social media and collaborative approaches for collecting input, provide some examples about who is doing what, what’s working, what’s not working, and why.

Visualizing Social Data to Improve Diplomacy

Leonard Lidov, President, Morningside Analytics

This talk will focus on how Dr. Lidov’s firm, Morningside Analytics, uses data visualization to understand public diplomacy, both in and outside government.  Morningside’s signature “dot-maps” picturing “Attentive Clusters” in the blogosphere have been featured in the media and opened business development doors in DC (http://online.wsj.com/article/SB124658422588090107.html ), but they are just one of several innovative approaches the firm uses to help clients understand how its network analyses can improve their understanding of how messages move in the online “Link Economy.

Using New Media for Citizen Engagement: Experiences from the General Services Administration

Leilani Martinez, Center for New Media & Citizen Engagement, U.S. General Services Administration (GSA)

This presentation will discuss several new media initiatives overseen by the Center for New Media & Citizen Engagement, part of the General Services Administration of the federal government. These will include discussions of developing tools, methods, and best practices related to using new media by government to engage citizens. Examples will include a citizen engagement tool used by 23 agencies to gather input for their open government plans, the Citizen Engagement Platform, and FedSpace, a secure intranet and collaborative workspace for government employees and contractors.

Supporting Lifelong Learning & Institutional Transformation with New Media

Michael Edson, Director of Web and New Media Strategy, Smithsonian Institution

The Smithsonian Institution’s Web and New Media Strategy that talks about an updated digital experience, a new learning model that helps people with their “lifelong learning journeys,” and the creation of a Smithsonian Commons-a new part of the Smithsonian’s digital presence dedicated to stimulating learning, creation, and innovation through open access to Smithsonian research, collections and communities. This talk describes the commons concept in the context of 21st century knowledge creation and the methods and drivers of organizational change.

Says who? Legitimacy in Online Collective Action: Enthusiasts and Interest Groups in Wiki Government

Scott Golder and Vladimir Barash, Cornell University

With the expansion of the World Wide Web, online communities have emerged focused on government and civic activities. These communities allow a wide user base to participate in everything from election campaigns to opinion polls to the legislative process (by making it easier for individuals to interact with members of local, state and federal government). The emergence of these communities has led to a greater citizen participation but has also opened up new venues for special interest groups to sway public opinion. For instance, politically oriented communities (dailykos, the free republic) advertise links to popular opinion polls and encourage their members to vote in such polls en masse, creating a cascade of skewed opinion. We explore the issues related to creating venues of open (often unregulated) online participation in the government process, and the role special interest groups play in these venues.

From Research of Social Media to Socially Mediated Research

Natasa Milic-Frayling, Principal Researcher and Director of Research Partnership, Microsoft Research, Cambridge UK

We are witnessing the ultimate assimilation of computing technology by the masses: millions of online users have adopted social media as part of their daily routine. At the same time, researchers are striving to understand the principles of sustaining social media and the implications the new practices have on research itself. In this presentation we discuss insights about two important aspects. First is the delicacy of social media design where seemingly small changes can cause a dramatic difference in the character of the online community. This applies to both UI features that facilitate interaction and the reward mechanism that administrators introduce to motivate specific behaviours. Second is the emergence of new methodologies that leverage the principles of social media. They are adopted by groups of individuals to achieve their common objectives. We illustrate how, for example, the issue of scale can be addressed through the use of games to mobilize a community of practice.

Health 2.0: Putting the Power of Open Science to the Task of Improving the Nation’s Health

Bradford Hesse, Chief, Health Comm & Informatics Research Branch, National Cancer Institute

Are social media sites data banks, secure repositories of personal assets, or data pimps, soliciting intimate exposure for profit?

I think these services need to choose.  I notice that the setting for who can see what in various systems is in flux.  I can set something to private today and may have to reset it keep it private later.

When I upload content to a site, shouldn’t the expectation be that the deposit is governed by the terms at the time of the contribution?  Why should terms change after I upload?  At least, shouldn’t new rules apply only to new content or content explicitly that has had permissions altered.

Banks do lend out the money I provide them, but only in an anonymous way.  No one knows my dollars are in their mortgage or car loan.  Only legally authorized entities can see my banking records (or so I hope).

Data pimps seem to want to give away anything I give up.  They sell my data as quickly and for as much as possible.

Banks have now developed a reputation that does not make them a great contrast for data pimps, but they still try to represent values like security, confidentiality, and reliability.

I have personally assumed that all data I upload is public.  Only my pictures of my kids have been made “private” and I would not be surprised if those pictures ultimately become public.

Photo credit: cambodia4kidsorg

Here is an example: http://twitpic.com/9rvfq

It provides a good illustration of the ways a person’s social network is clumped into clusters built around life phases, workplaces, educational institutions, teams and locations.  As people move through more of these stages of life during the Facebook era (and often before) they accumulate these clusters.

Facebook or other contact and friend management systems might could leverage this clustering to organize the presentation of contact information streams.

Bernie recently announced on the SOCNET list that he has updated his script for downloading your Facebook network.

“Features:

1. Its faster. (Presently orders of magnitude faster than Nexus, Touchgraph or ORA).
2. It gives nice feedback during the download.
3. It has less bugs!
4. It gives you the output as a file you can right-click and save rather than copy-paste.
5. IDs are names.”

Bernie writes that phase two of his project is underway.

Bernie is planning a demo at the Sunbelt social network analysis conference in Italy in 2010.

Bernie is the author of the Facebook chapter in our forthcoming book Analyzing Social Media Networks with NodeXL: Insights from a connected world available from Morgan-Kaufmann in July 2010.

Saving Our Present for the Future: Personal Archiving 2010

From family photographs and personal papers to health and financial information, vital personal records are becoming digital. At the same time, creation and capture of new digital information has become a part of the daily routine for hundreds of millions of people. But what are the long term prospects for this data?

The combination of new capture devices (more than 1 billion camera phones will be sold in 2010) with the move from older forms of media is reshaping both our personal and collective memories. The size and complexity of personal collections growing, these collections are spread across different media (including film and paper!), and the lines between personal and professional, published and unpublished are being redrawn.

Whether these issues are described as personal archiving, lifestreams, personal digital heritage, preserving digital lives, scrapbooking, or managing intellectual estates, they present major challenges for both individuals and institutions: data loss is a nearly universal experience, whether it is due to hardware failure, obsolescence, user error, lack of institutional support, or any one of many other reasons. Some of these losses may not matter; but the early work  of the Nobel prize winners of the 2030s is likely to be digital today, and therefore at risk in ways that previous scientific and literary creations were not. And it isn’t just Nobel winners that matter: the lives of all of us will be preserved in ways not previously possible.

On Tuesday, February 16, the Internet Archive will host a small conference for practitioners in personal digital archiving.

The morning sessions will be devoted to examples of current practice; the afternoon discussion will focus on developing recommendations for institutions and individuals, and on developing a research agenda. Among the questions we would like to discuss:

- What new social norms around preservation, access, and disclosure are emerging?
- How can we cope with the shift from simple (e.g. text) to rich media (e.g. moving images) in personal collections?
- What is the gap between current possibilities for preserving personal collections, and what is actually needed by both individuals and institutions?
- What tools and services are needed to better enable self-archiving?
- What new economic models to support personal archives may be evolve?
- What are the long term rights management issues? Are there unrecognized stakeholders we should begin to account for now?
- Can we better anticipate (and measure) losses of personal material?
- Do libraries, museums, and archives have a new responsibility to collect personal materials?
- What has already failed? Can we generalize about approaches that are likely to fail over time?
- What are the options for cultural heritage institutions — libraries, museums, and archives — that want to preserve the personal collections of citizens and scholars, creators and actors?
- What might be the risks of building archiving systems that are “too good” or overly applied?

For individuals, institutions, investors, entrepreneurs, and funding agencies thinking about how best to address these issues, this meeting will include a variety of examples that may be replicated, and will sharpen the questions (technical, social, economic) around personal archiving.

For further information, please contact Jeff Ubois (jeff@ubois.com).

NodeXL updated starting with version 1.05 with features that make it fairly easy to create basic “Venn Diagrams”.  A Venn diagram is a familiar way to illustrate the overlap (or lack thereof) of two or more “sets” of things.

There are some very amusing Venn diagrams out there!  This one in particular made me laugh but I may be dating myself.

The Venn diagram feature is a special request from the Microsoft Biological Foundation group.

A Venn is related to but different from an Euler diagram.  An “n-Venn” diagram is a collection of closed curves (“circles”) on a plane where all the circles intersect. A “simple” Venn diagram has just two circles but complex diagrams can have more.  A 2 circle Venn diagram has 3 regions (A, B, A+B) and a 3 circle Venn diagram has 7 regions (A, B, C, AB, AC, BC, ABC).

A Survey of Venn Diagrams can be found at http://www.combinatorics.org/Surveys/ds5/VennEJC.html.

Our implementation is a bit of a hack, we basically let you define the X/Y location of 3 circles.  A richer Venn tool would make it easy to take set data and define these circles.  We may get that implemented in the coming months.

NodeXL has had a rudimentary flickr tag network data spigot for some time but we have just added a number of features to this data importer that makes it much more useful.

You can now select the number of network levels to include, an optional sample image file can be included for each tag, and the dialog now provides feedback as it requests the various parts of the network from Flickr.

The tag network generates maps like the following set of connections among terms related to “sociology”: