Biological Networks for CIO's to consider

Fred Hapgood about Biological Networks in the Tomorrow's Buzz Today blog at CIO.com

Networks used to be comprehensible; you could understand their parts and how they worked together, and, because you did, they were controllable in a very basic, mechanical way. But utilization rates, numbers of nodes, and application types have increased every year, sometimes exponentially, always significantly, and the trend shows every sign of continuing until retirement. Networks are steadily becoming more chaotic and harder to control.

Everyone's first thought about the right way to fix this problem, says Fred Hapgood, is to retain today's general outlook and just automate it. However, some researchers have noticed that biology is rich with large networks — such as protein cascades and gene switching networks — and seems to have no trouble extracting wonderfully adaptive and robust behaviors out of all these systems. Take a couple of minutes to step away from your current hardware challenges and check out what scientists say may be coming next.

The McKinsey Quarterly: Creation nets: Getting the most from open innovation

The McKinsey Quarterly has a piece on Creation nets: Getting the most from open innovation.  The abstract describes this as

• Most executives are by now familiar with open innovation: the idea that companies, by looking outside their own boundaries, can gain better access to ideas, knowledge, and technology than they would have if they relied solely on their own resources.
• Despite the attractions of open innovation—and its successes in areas such as open-source software development—few companies believe that they know the best way of creating value with the open model of innovation.
• Companies must go to the peripheries of today's commercial and scientific endeavors, where hundreds and even thousands of collaborators from diverse institutional settings are participating in innovative "networks of creation."
• Managers can use the principles and mechanisms of "creation nets" to profit from open innovation and to create more value than would be possible with the closed model of innovation.

You will need a subscription (or a library) to see the full article.

Connectivism: Learning as Network-Creation

George Siemens has an article in ASTD's Learning Circuits, "Connectivism: Learning as Network-Creation"

The domain of learning is significantly hampered by progressive revisions of what it means to learn, to know, and to understand. A subset of connectivism, network forming, is presented as an accurate model for addressing how people learn. The test of any theory is the degree to which it solves problems and incongruities within a domain. The shortcomings of behaviorist, cognitivist, and constructivist ideologies of learning are answered in light of learning as a connection-forming (network-creation) process.

Time, Identity and Social Networks

I have posted an article to piecing IT together - Time, Identity and Social Networks. In it I begin an exploration of the relationship between common perceptions of time and social networks.

In upcomming weeks I will be exploring these ideas further at my personal blog and also hope to announce the launch of a number of related website projects to test these ideas.

Feedback, comments, criticism and suggestions are very welcome!

MacArthur recognizes the importance of networks

Jon Kleinberg of Cornell, has received one of this year's MacArthur Fellow Awards ("Genius Grants").  Great news for the importance of networks in the world.  From the Jon Kleinberg profile at the MacArthur website:

Jon Kleinberg is a computer scientist with a reputation for tackling important, practical problems and, in the process, deriving deep mathematical insights. His research spans diverse topics ranging from computer networking analysis and routing, to data mining, to comparative genomics and protein structure. He is best known for his contributions to two aspects of network theory: "small worlds" and searching the World Wide Web.

SNA used to capture Saddam Hussein

Bruce Hoppe points to some interesting SNA used to capture Saddam Hussein

Many thanks to David Koelle at Charles River Analytics for sharing this headline with me: "Sociological skills used in the capture of Saddam Hussein." (Published just last month in Footnotes, the newsletter of the American Sociological Association.)

The article profiles the impressive work of of Major Brian J. Reed: "He reports using a layered social network analysis to locate Hussein prior to his capture. 'The intelligence background and link diagrams that we built were rooted in the concepts of network analysis. We constructed an elaborate product that traced the tribal and family linkages of Saddam Hussein thereby allowing us to focus on certain individuals who may have had (or presently had) close ties to [him],' said Reed."

Connectivism: Learning as Network-Creation

Connectivism: Learning as Network-Creation

Existing theories of a particular subject matter are typically revised and adjusted to reflect changing environments. At some point, due to continual revisions, the theories becomes so dichotomous and complex that it is no longer reflective of the subject it is intended to define and explain. At this point, the existing theories need to be replaced with models that more accurately reflect the link between theory and reality. The domain of learning is significantly hampered by progressive revisions of what it means to learn, to know, and to understand. A subset of connectivism, network forming, is presented as an accurate model for addressing how people learn. The test of any theory is the degree to which it solves problems and incongruities within a domain. The shortcomings of behaviourist, cognitivist, and constructivist ideologies of learning are answered in light of learning as a connection-forming (network-creation) process.

Endless Knots

From Bill Ives at Portals and KM: Endless Knots - Jessica Lipnack

Here is a nice new blog, Endless Knots, by Jessica Lipnack, a writer of both fiction, non-fiction, and books on networking. The latter is through her firm, Netage. There is a series of posts describing her experience at a summer writer’s workshop. I have always wanted to attend one of these events and have not been able to do so yet. I am sure more good writing will be found here.

Network-centric business

Mopsos quotes an interview with Prof. Manuel Castells concludes thusly, Network-centric business

Now this is exactly what I would like to see happening in our large organizations: moving from vertical and rigid bureaucracies to horizontal living and interconnected networks. Imagine local teams of information-oriented (more than sales-oriented) people, and back offices of specialized teams, or "Value Shops", as Tom Stewart puts it. And I think the key is not so much in the technology than in what Prof. Castells calls the "programming of the network" .

Informal learning = Network learning

George Siemens looks at an article on informal learning from Fast Company and sees a network appear in how we acquire knowledge: Informal Learning

This concept of network learning answers many questions about how we acquire much of our knowledge (even elements that contradict each other). When we exist in a knowledge climate (or network), we constantly scan, evaluate, and select for use, elements that answer questions with which we are struggling. Some elements of learning will relate to our values, attitudes, and beliefs, others will relate more concretely to how we perform our work. In an election season, politicians rely heavily on "teaching" the electorate through a network imbued with their message. If the electorate is unwilling to accept the message directly, perhaps it will accept the message when embedded in our existing learning network (i.e. an unpalatable concept is more attractive when it links (even if inaccurately) to our existing values and lines of reasoning). Perhaps as educators, we need to become more aware of how people learn from their network. Often, I imagine, our formal instruction competes with information sources in their existing learning network (particularly relating to soft skills).

Cross' Network Roundtable

From Bruce Hoppe: The Network Roundtable is off and running

Rob Cross recently kicked off the Network Roundtable at the University of Virginia. Stay tuned to this initiative over the coming months; it is sure to generate useful insights in driving business results with the power of social network analysis. There are six applied research projects already underway:

• Client Connectivity: Generating Value at the Client Interface with Network Analysis
• Innovation: Driving Innovation and Top Line Revenue Growth with a Network Perspective
• Leadership Development: Enhancing Leadership Effectiveness and Resilience via Network Management
• Organizational Change: Facilitating Large Scale Change with a Network Perspective
• Well-Being at Work: Promoting Employee Well-Being through Relational Constellations at Work
• Communities of Practice: Assessing and Supporting Communities of Practice with Network Analysis

SNA in Marketing

A great resource for SNA articles related to Marketing was sent to the SOCNET mailing list.

In preparation for MeshForum 2005's panel on Networks and Sales, this list offers a fantastic collection of articles and resources on the subject of applying Social Network Analysis to marketing challenges.

Paper on viral networking

McGee's Musings

Jim McGee, along with many others have recently noted a paper from MIT on viral networking. The paper is a bit old (dated 2003) but still relevant and useful in looking at the future of "viral" or "mesh" networks (from a technical sense) involving wireless/radio networking.

Detecting networks

[cond-mat/0309508] Fast algorithm for detecting community structure in networks

An abstract and paper on a technique for detecting network structures in large scale datasets. The paper itself looks highly interesting. But as well how I found this article is, itself, of interest.

The article was found from the following source:

http://www.technorati.com/tag/networks

Which is a demonstration of Technorati's recent "tag" feature. Specifically I found the article via the set of links Technorati displayed that were pulled from Furl and Del.icio.us.

A simple, yet highly effective way to harness the collective knowledge and wisdom of the network for, in this case, discovering new sources and articles etc on networks.

Networks enhance and detract

In the comments to our definitions of network, Sheizaf Rafaeli gives three additional versions of the definition of network.

A network is a net. In sports, a "net" is a barrier. Net is also that which remains after all deductions and adjustments are made. A third etymological derivation for net is a means of entrapment, surrounding and captivation. Among all interpretations of the "net" in "network" this third meaning is, in our view, the most appropriate.

A funny thing about that third definition with regard to human behavior: The net that holds me up and supports me (people, institutions, background) is the same net that can "entrap or captivate" me just as easily. In reading The Medici Effect by Frans Johansson, there are chapters entitled "Break out of Your Network" and "How to Leave the Network Behind" that talk about the potentially detrimental effect a network can have on people who seek to be creating new things.

Applied Networks - Challenges to consider for MeshForum

Considering a network-centric perspective is what MeshForum is intended to be all about. By bringing together experts from a wide range of fields, we're seeking to spark conversations, discussions, and hopefully new solutions to old problems.

Towards that end, I am proposing a set of "Big Challenges" which involve Network theory, might challenge pre-conceptions of one (or more) industries, and hopefully might be open to new solutions via the application of techniques, tools, and ways of thinking from other fields. All with, of course, a strong Networks aspect.

First - Commercial Air Travel.

Problem: Much of the commerical air industry even during a time of fairly heavy travel is suffering financially and in the stock market. I'm most aware of the situation in the US, but similar problems and challenges are true worldwide.

Historically the air travel industry has been bifurcated and heavily regulated. The same carriers carry both people and cargo (the exception being some newer airlines such as SouthWest and some alternative airtravel options such as FlexJets and the like which serve small airports mostly). Fares and schedules are the result of massively complex software with a long historical basis. Complex optimization schemes attempt to calculate the "best" solution to a vast network problem - which planes, crews, cargos, and passengers will combine to both "work" as a schedule (i.e. not require more planes, terminal slots, or crew hours than are physically available) and be profitable (i.e. ideally by some means of setting prices result in planes that collectively are profitable to opperate).

These systems are vast, complicated and embedded into many aspects of the travel industry. But clearly, the example of some of the newer carriers points out these are not the only ways to do business - flat fares, simplified seat classes (or even only one class) and a service emphasis can and seemingly do demonstrate a high degree of profitability as well.

So, the challenge is - Can network techniques from other fields help model this multi-varient problem, suggest new alternative solutions, and perhaps offer out of the box solutions to the problem facing the airline industry (and as a result the problems facing many travellers in these days of airline bankruptcy and uncertainty)?

See Doc Searls' post from Dec 6th for a related conversation.

Second - a problem that reoccurs across many areas of networks. How can networks be talked about (and used) when the network is changing more rapidly than it is possible to map and analyze it?

Whether trying to map out a social network made up of people who are interacting (and thus changing opinions of and relationships with each other) or more broadly looking at how a marketing message can spread or how to handle representing and optimizing a distribution network where demand and usage changes over time.

In general terms it can be thought of as a problem of dealing with networks over time - representing networks which change and which are also large enough and complex enough that the time to map and traverse them is less than the frequency at which they change (in at least some respect).

This may also imply that the network links (and perhaps nodes) are not of long duration and stable connections, but are of some form that changes, in at least some aspect, on a regular and probably somewhat frequent basis.

How is this problem dealt with in more controllable networks? Such as IP networks where nodes and/or connections fail on a regular basis and/or are added/modified and yet the whole network has to be navigable and useful at all times.

Third - a challenge related to the second challenge, but subtly different. How can "networks" be worked with, mapped, navigated, and predictions made about them when either connections between nodes are not uniform (i.e. can be represented via different degrees or perhaps as either one way or bi-directional) and when perhaps the "nodes" may be of very different characteristics. Many network problems whether biological, social, or otherwise are loosely talked about using a wide range of possible node types (in biological systems these might be some nodes that represent various chemicals while others that represent cells, elements of cells, drugs, viruses etc) in a social network nodes often are people but frequently groups, departments, locations, organizations, companies, schools, etc may also be included in the mapping.

Does this change the network theory in any important ways?

In upcomming days I'll post other possible "big" challenges for MeshForum to consider. Your feedback, comments, suggestions, and links are very welcome!

Entrepreneurial networking and alliances

In Dave Pollard's How to Save the World, he writes about Entrepreneurial networking and alliances

Two of the fundamental principles of business are: Relationships trump credentials in buying (and many other business decisions), and It's not what you know, it's who you know that counts. These truisms show just how important business networking is, especially in an enterprise that doesn't have a lot of people or spare time to invest in relationship-building.

Let's start with some definitions: Networking is the process of building and nurturing business relationships. Alliances are contractual arrangements between two or more businesses to achieve shared objectives, usually with a limited life.

More about the value of networking and alliances for business in the rest of his article.

Networks, Complexity & Emergence

An excellent entry on the nature of networks from the end of 2003. Monkeymagic: Networks, Compexity & Emergence

Networks often (maybe always?) exhibit emergent behaviour. Emergence is another buzzword, but less flakey than memes. (It's got a thousand year history for a start!). Anyway, I know I've said networks is the next sensible place to start examining for, but network science is very much a subset of complexity theory.

Collaboration : greatest value dynamic of networking age

Interested in networks and collaboration? Check this project that seems to be from KnowledgeBoard. Collaboration : greatest value dynamic of networking age

Would your professional network like to collaborate on contributing a chapter to a book on Collaboration? Tell us your network coordinates if you might be interested. Meanwhile this thread will discuss some of the sorts of chapters we want to find networks and writers to adopt...what are we missing

Defending Networks against cascading failure

DEFENDING NETWORKS AGAINST CASCADING FAILURE. Just as foresters can
often halt a forest fire from burning out of control by deliberately
setting firebreaks, it might be possible to reduce the size or
spread of outages in a network in the wake of an attack or
overload. The Internet and the electrical grid are just two such
networks that might benefit from a new model devised by Adilson
Motter of the Max Planck Institute for the Physics of Complex
Systems in Dresden. Several previous network models have shown how
an attack on key nodes of a system can cascade into a catastrophic
failure. Motter's model shows how such a failure can be mitigated
by shutting down selected peripheral nodes that handle only small
amounts of the network's total load. Simulating attacks on networks
showed that answering the original attack with several successive
rounds of precautionary node shut-down drastically reduced the size
of the overall cascade. (Physical Review Letters, upcoming article;
motter@mpipks-dresden.mpg.de)

Excerted from a copy of Physics News update (received via another mailing list)

This is of interest to MeshForum participants as it points to the value of theortical research being shared with practitioners, this type of approach, if confirmed, could lead to new advances in management of power grids, TCP/IP networks, perhaps even air travel grids in the face of failures of hubs, indeed many other networks might make use ot this advance.

boingboing on Political Blog researc

Boing Boing: Political bloggers don't follow the power-law distribution

Interesting link on BoingBoing to a paper showing how a commonly written about network, online Blogs, can, on closer examination present a more complex and different picture than usually depicted. Specifically, by not following a "power law" distribution, political blogs point to the possibility that even in networks with apparent winners alternatives may be available. In the case of political blogs I would argue the schedule and nature of campaigns and perhaps the influence of non-blog sites (such as various campaign's own sites) may account for much of what the researchers discovered.

Exactly the type of research and discussion we want to see at MeshForum

Power of reputation in your network

Connectedness: Reputation and Trust (aka "Network Closure")

The power of reputation rests on the idea of network closure, which is the degree to which everyone knows everyone else in a network. In a subgroup or "clique" where everybody knows everybody else, reputation can have currency much more powerful than money. Promises within the group can be trusted because the consequences of breaking a promise would be catastrophic. Anyone who mistreated a fellow member in such a group would quickly find himself ostracized by the entire group, his reputation ruined.
[via elearnspace]

Network Analysis of Knowledge Construction in Asynchronous Learning Networks

From the Journal of Asynchronous Learning Networks comes an article on Network Analysis of Knowledge Construction in Asynchronous Learning Networks by Reuven Aviv, Zippy Erlich, Gilad Ravid, and Aviva Geva at the Open University of Israel.

ABSTRACT: Asynchronous Learning Networks (ALNs) make the process of collaboration more transparent, because a transcript of conference messages can be used to assess individual roles and contributions and the collaborative process itself. This study considers three aspects of ALNs: the design; the quality of the resulting knowledge construction process; and cohesion, role and power network structures. The design is evaluated according to the Social Interdependence Theory of Cooperative Learning. The quality of the knowledge construction process is evaluated through Content Analysis; and the network structures are analyzed using Social Network Analysis of the response relations among participants during online discussions. In this research we analyze data from two three-month-long ALN academic university courses: a formal, structured, closed forum and an informal, non-structured, open forum. We found that in the structured ALN, the knowledge construction process reached a very high phase of critical thinking and developed cohesive cliques. The students took on bridging and triggering roles, while the tutor had relatively little power. In the non-structured ALN, the knowledge construction process reached a low phase of cognitive activity; few cliques were constructed; most of the students took on the passive role of teacher-followers; and the tutor was at the center of activity. These differences are statistically significant. We conclude that a well-designed ALN develops significant, distinct cohesion, and role and power structures lead the knowledge construction process to high phases of critical thinking.

[via elearnspace]

Structural holes and gaps in your network

David Teten has two recent posts about structural holes, looking at the benefits and hazards of holes, or gaps, in your social network.

On structural holes

You will usually benefit if the members of your network do not know one another. Ronald Burt, in his innovative and influential book, Structural Holes: The Social Structure of Competition, provides fascinating support for the argument that both people and companies benefit by sitting in a "structural hole" of a network. A structural hole exists when there is only a weak connection between two clusters of densely connected people.

And on the other side. More thoughts on structural holes and closed networks

[paraphrase] There are two benefits of membership in a closed network: 1) Improves access to information. 2) Closed networks make it easier to reward and punish people, which in turn makes it less risky to trust other members.

Weblog networks as social ecosystems

Lilia Efimova has posted the summary of some of her thinking about how weblogs are more than "a bunch of linked egocentric websites." Her article Weblog networks as social ecosystems lists five main features with attached graphics. Go there to see the pictures.

1. Weblogs are online identities of their authors: by reading weblog we learn about and connect with another person


2. Networking. Via weblogs a reader get introduced to a blog author network


3. Weblog networkds serve as peer-filtering and recommendation engines: they help interesting ideas travel faster


4. Distributed conversations. Weblog conversations do exist, but they are distributed, difficult to track and different from other technology-mediated conversations


5. Connecting with community. By connecting with several weblogs belonging to a dense weblog network new blogger connects with a community.

Types of Networks

Networks, the focus of MeshForum is a term that holds many different meanings, generally context specific.

Much of the literature on Networks focuses on either a specific type of network, generally within a very specific context, or on properties and traits of all "networks". While important, this is not all that needs to be thought about when thinking about Networks, nor does it sum up all of what will be covered at MeshForum.

Very broadly "Network" can both be a noun and a verb. As a noun, "Network" is some system of "nodes" and "links". As a verb, "Network" generally means creating links between nodes.

However, a number of important distinctions are missed by these basic definitions. One key distinction, often glossed over, is how a "network" changes over time. Most networks are dynamic and change from moment to moment, however much of the research on networks deals with questions about a static snapshot of a particular network.

Another key distinction is between "infrastructure" style networks - where the nodes and the "links" are of a long duration (Examples of this would be a street map, power grid, many IP based computer networks) and "dynamic" networks where nodes and "links" are rapidly changing and highly variable (Examples of this would be many economic systems where customers, exchanges of value, and items being purchased change hands frequently and often; other examples might be technical "mesh" networks where nodes and links are established on the fly and as needed, or many social networks where friendships and communications with friends change frequently - consider a nightclub as an example).

When looking at analyzing networks it is also important to remember and realize that many times there are multiple networks (or at least many different ways of looking at and tracking the data) that overlap and interact. Consider the case of electrical distribution.

On the one hand, the physical infrastructure of the power grid is fairly static - most "nodes" are large, phyisical structures that stay in place for a very long duration (power plants, power lines, transformers, meters, etc). On the other hand, consumption and "customers" as well as the economic and legal structures "owning" each part of the power grid can and do change rapidly and frequently. Companies are bought and sold everyday, customers move, seasons change, usage differs, in short the "network" when extended away from the broad infrastructure of the power grid and into the network of customers and companies becomes highly dynamic and changing.

If, for example, you are analyzing such a network to look at how changing the legal environment (say regulating prices) might impact the system; or if you are looking at how the introduction of new technology such as powercells where consumers might generate power vs. consume power, you have to keep in mind that there are many related networks interacting. Thus, while looking at and anlyzing the longlasting infrastructure elements is important, you have to also consider how to capture, represent, and study rapidly changing aspects of the network.

In general, infrastucture type networks are longlasting and fairly stable, thus more prone to being easily analyzed and studied. For one, it is possible to map the network, identifying the nodes and the links between the nodes with some assurance that the result is a very close representation of something real. In dynamic networks, however, as the nodes and links between the nodes can change, disappear or be added very rapidly, any attempt to map the whole network is difficult and potentially nearly impossible.

The nature of "links" and what is meant by them is also different. An infrastucture style network can be thought of as really three elements, nodes, links, and information being passed along the links. In the case of a powergrid, information in the form of "power" could be thought of as starting from one node and moving across links to some other node. More generally, in an infrastructure style network, the "action" of nodes interacting can occur other than by forming/destroying links - links can in some manner of speaking be "used". In most infrastructure networks, links are usually multidirectional, thus "action" can occur from either node connected to the other node.

On the otherhand, in a dynamic network "links" might be thought of as being highly fragile, they could be "created" as the act of use and immediately destroyed. As well, even more so than with infrastructure style networks, "links" in a dynamic network can be unidirectional - connecting one node to a particular other node, but not therefore connecting back to the original node. Thus in a dynamic network the direction of "connection" is critical for resolving quesitons about paths between nodes.

Taking this rough model and applying it to "Networks" such as the ones thought about and discussed in the "Social Network" field begins to illustrate the challenges faced by any attempt to "map" such networks. As well, it may help separate out the multiple networks that are, in fact, being looked at when social network analysis is performed.

At MeshForum we will be exploring these questions and many more, focusing on specific case studies of certain types of "Networks" as well as on the general questions raised when studying networks.

Consider the "Networks" you and your organization are a part of? Are they infrastructure networks? Dynamic Networks? Or some of both? When you think about what a "link" and a "node" are in these networks, what do you mean by "connecting"? How are these Networks you are a part of used? What challenges have you overcome around these Networks? What would you like to understand and overcome in the future?

The Network is the Market

An article from Ross Mayfield in August 2003 saying The Network is the Market

Social Networks (unlike Political or Creative Networks) are fundamentally transactional. We each have a group of people, no larger that 150, that we passively track and trade with. We have relationships of a kind with each of them and are aware of their relationships with each other. What we are monitoring is social capital. When someone wrongs another, if you have both people in your Social Network, you become aware of it and adjust your tacit social credit ratings.

MS Social Computing Symposium

Microsoft Research Social Computing Symposium 2004

A conference held this month (happening as this is being posted) by Microsoft, but in collaboration with groups from IBM and FX Palo Alto.

Up to 75 people, all "leaders in the field of social computer and social software"

It is being blogged by a number of folks.

Paper: Structure in Personal Networks

JoSS: Journal of Social Structure has an article on Structure in Personal Networks
by Christopher McCarty of Bureau of Economic and Business Research, University of Florida.

ABSTRACT: Most personal (egocentric) network studies describe networks using measures that are not structural, opting instead for attribute-based analyses that summarize the relationships of the respondent to network members. Those researchers that used structural measures have done so on networks of less than 10 members who represent the network core. Although much has been learned by focusing on attribute-based analyses of personal network data, the application of structural analyses that are traditionally used on whole (sociocentric) network data may prove fruitful. The utility of this approach becomes apparent when the sample of network members elicited is relatively large.
Forty-six respondents free-listed 60 network members and evaluated tie strength between all 1,770 unique pairs of members. Graph-based measures of cohesion and subgroups revealed variability in the personal network structure. Non-hierarchical clustering generated subgroups that were subsequently verified by respondents as meaningful. Further analysis of the correlation between subgroup types and overlap between subgroups demonstrates how the analysis of each network can be summarized across subjects. Four case studies are presented to illustrate the richness of the data and the value of contrasting individual matrix results to the norm as defined by all 45 subjects.

The State of Networking

The nettime mailing list has been having an interesting discussion, following a post by Geert Lovink and Florian Schneider. The archives are fully available. The State of Networking (with Florian Schneider):

No longer the society, the political party or even the movement, networks are the emerging form of organization of our time. By marching through the institutions the idea of networking has lost its mysterious and subversive character. Sandpapered by legions of consultants, supervisors, and sociologists, as a buzzword networking superseded the latest fashions of sustainability, outsourcing, and lean organization.

Letter from Wonderfall's producer, Networks (tv) networking

My friend Mary Anne Mohanraj kept a "blog" for about 6 years or so before the term was created (since 1995 or so), this morning (Friday Mar. 19th) she posted a letter from the producer of a new show on Fox, Wonderfalls.

Friday March 19th, Wonderfall's letter

I am linking to it here on MeshForum for two reasons.

One - it is an example of a multiplicy of uses of "Network" - both as in "Fox Network" and as in "networking the fan community", the producer is explicitedly trying to spark a friend-of-friend network effect to support his newest show, and building on his past experiences.

Two - MeshForum should find a way to incorporate both of these activities into our conference - both the "Networks" ideally from an insider's perspective, and the adhoc social networks that they or at least their shows create.

A Networked World

A Networked World - a blog by Earl Mardle: "In a Networked World, There Really Is No-one In Charge"

Communities and Dubar's Number

Mopsos - Communities of practice and Dunbar's number

Dunbar is an anthropologist at the University College of London who hypothesized that there is a cognitive limit to the number of individuals with whom any one person can maintain stable relationships, and predicted that 150 is the "mean group size" for humans.

How News Travels on the Internet

Stephen VanDyke on How News Travels on the Internet. Both network and time have a role to play in this. Check the larger discussion generated by his thinking (comments, trackbacks, and additional thoughts by Stephen).

Living Machines - Wired Magazine Feb 2004

Wired 12.02: Living Machines

A series of 8 short articles in the February 2004 issue of Wired Magazine. The focus is on how technology and biology are converging, much of this involves complexity and a network perspective. Many of the authors of these short pieces have upcoming books on related subjects.

Six Degrees of Project Management

Six Degrees of Project Management

Article and calculator from Baseline Magazine on doing SNA to help project teams work together better.

Network pictures

Any of these look like traditional org charts to you? collects a number of network visualizations. We need a pretty picture for this site.

Introduction to Social Network Analysis

Rob Cross | Social Network Analysis (thanks to Corante's Many-to-Many for the link)

An introduction to Social Network Analysis by Rob Cross of the University of Virginia. Especially notable is the case studies he cites of using Social Network Analysis in a business context.

I got a guy... (Chicago Tribune article)

Chicago Tribune | I got a guy, you got a guy ...

A reminder than networks are a very old phenomenon, and that weak ties matter a great deal. Read over the article carefully, almost every "guy" mentioned is not a strong personal connection, but a friend of a friend of a friend, and usually a "weak" tie at that.

As the author mentions, these are not examples of corruption persay, but rather "how things get done". It is easy to think that software will eventually map out networks completely, but keep in mind that most "guys" are not easily mapped out, but the result of conversations and casual conversations.

Great article.

Meskill: musings on autonomic social & knowledge networks...

Charles Kadushin intro to social network theory

From the Introduction to a draft of Chapter 2 (pdf) of Charles Kadushin's book on Social Networks:

Social network theory is one of the few if perhaps the only theory in social science that is not reductionist. The theory applies to a variety of levels of analysis from small groups to entire global systems. To be sure, there are emergent properties at different system levels, but these are extensions of what can be done at a lower level and not entirely different forms of organization. This chapter will introduce a minimal set of concepts used in network theory. The concepts apply to all levels of networks. Some illustrations and a few elementary propositions will be offered for each concept to suggest that the concept is useful. Further applications of the concepts as well as more complex concepts and propositions will be developed in chapters that are devoted to specific substantive subjects. While all the concepts to be introduced also have formalized ways to measure them, and often several different ways to measure the same concept, the aim of this book is to develop the concept itself and show how it is applied in theoretical statements and in substantive applications. Measurement issues will be noted and referenced, but “how to do it” is reserved for other literature.

Commonwealth Club event on Social Networking

Summation: Upcoming Commonwealth Club event on social networking

Auren Hoffman moderates a great panel of speakers on social networks. If you are in Palo Alto looks well worth attending.

Difference between communities and networks

Many-to-Many discusses a framework to explain The Difference Between Communities and Networks.

Lurking and Social Networks

Ton Zijlstra has some interesting thoughts about how lurking affects networks. This is a discussion in progress. Ton's Interdependent Thoughts: Lurking and Social Networks