Here Is the updated proposal

Electronic Culture Project Proposal


Background Context
In 2002, The BC liberal government passed legislation to dissolve the entity
formally known as Tech BC and have SFU take over the programs that were offered
there. Over the last few months the task of integrating three new departments
(IT, IA, M&T) into the SFU fold, has fostered a discourse around the role of
structure in academic institutions. Many ardently oppose the adoption of SFU’s
established structure, arguing that the universities current approach to
classifying academic departments serves little purpose outside of maintaining
formal hierarchies, and clear divisions of authority. This argument goes on to
point out that SFU’s structured, rigid approach to managing different knowledge
domains is indicative of a modernist approach to higher learning that is simply
no longer relevant to our contemporary social and cultural needs.

Problem Definition
what’s clear to those who champion change over convention is that advances in
today’s world require a convergence of knowledge across many disciplines. For
this reason, meaningful research and innovation cannot, and will not move
forward unless we make a concerted effort to promote and maintain collaborative
relationships and knowledge synergies. The critical bottle-necks of the
information age are no longer about transmission speed and processing power, but
rather the ineffective sharing of information and skills across multiple
knowledge disciplines.
Unfortunately, the bureaucrats, and academic politicians have become so caught
up in their fight to maintain power that they fail to see how their inability to
accept change could potentially contribute to the stifling of social and
cultural evolution.

Project Aim
The primary goal of this work is to address the issue of the importance of
embracing new approaches to learning so that social and cultural evolution can
be expedited in as efficient a manner as possible.

Proposed Solution
In a complex system, evolution is a process that cannot be stopped. Innovation
and changes will always take place. However, these innovations may not occur at
an optimal rate. In order to harness the full potential of Universities as
centers for innovation, we would like to implement an approach that will enable
people to take patterns of positive emergent behavior from these academic
institutions that could drive the next phase of evolutionary innovative changes.


Here is the model of our proposed solution

We envision the School of X as a connected node that exists within SFU. The
School of X will inherently act as an experimental ground whereby unfettered
innovation is allowed to take place within the structure of the University. This
unrestrained innovation will take place for a defined period of time. At the end
of each innovation period, we will take the time to reflect back and extract
patterns that had emerged. There will no doubt be positive as well as negative
emergent patterns. These patterns will be thoroughly analyzed and packaged in
the form of pattern language as blueprints that could be introduced into realms
outside of the School of X—SFU and eventually the society.

For the purpose of this assignment, we will be extracting patterns from our
experience at TechBC. The reasons why we chose TechBC is because we acknowledge
the fact that this University was able to experiment with new and innovative educational approaches within its 3 years of existence. Thus there
will be a lot of valuable patterns that could be extracted out of our 3 years
experience at this school.

Cheers, Dale

A model of our work

Hey hey hey



As Laura has asked, we have articulated our project as a visual model. The key emphasis in this model is the notion of using pattern languages to distribute and share knowledge in an easy and effective manner. As you look at the model note that the square blocks are patterns, and that the blocks consolidate to create a language of patterns. Of importance here is the idea that individual patterns do not exist on their own. In reality a pattern is a component part of a network of patterns, and as patterns come together they coallesce to create even larger patterns, which can be thought of as languages. We have tried to articulate this in our model using squares. Hopefully that translates well. What we would like to explore is the idea that Pattern languages from different disciplines can come together to create a strong platform for knowledge sharing--both in the academic enviornment as well as society on the whole. The beauty of patterns is that they are constructed using simple and easy to understand language--an approach that is in keeping with the ideals of the third culture.

The second thing to note in this model is the manner in which we have situated the school of X at the forefront of a movement. This is meant to articulate the idea that universities are crucibles of innovation and that research in these intstitutions provides the impetus for social change and evolution on the whole. In the model we are attempting to visualize the importance of using pattern languages to expedite this process. If you look towards the top of the diagram you will notice that we have included a time scale--you''ll probably recoginze it from the models Laura linked to in the first week of mod three. Note that the points of signficnace on this time scale are getting closer togther. Also note that the edge of the collective circles (society, academics, sfu, school of X) are just about in line with a major step event on the time scale. This is our first attempt at representing the pending phase shift, and the fact that we feel the school of x will be a major player in bringing other player towards that shift. An important point to consdier here is the way that with model has indicated that a portion of society, as well as a portion of sfu, and academics is ahead of the school of X. The idea here is that the school of X is not the only important player in the move towards change.

Got to go for know more to come later

Dale

Yeah...what Jeremy Said

In my research for the project I came across this fantastic qoute from Jeremy Rifkins book The Age of Access. Give it a read.... its does a great job articulating my current perspective.

"Hierarchical organizations work best in periods of steady and stable markets but are woefully inadequate in periods of flux. Their administrative procedures are far too rigid to adjust to rapid changes in market conditions.
Networks, on the other hand, are far more flexible and better suited to the volatile nature of the new global economy. Cooperation and team approaches to problem solving allow the partners to respond more quickly to changes in the external environment. While the players give up a degree of autonomy and sovereignty, the spontaneity and creativity that flow from network-based collaboration give them a collective edge in the new more demanding high-tech economy. Because networks involve complex channels of communications, diverse perspectives, parallel processing of information, continuous feedback, and reward thinking “outside the box”, the players are more likely to make new connections, generate new ideas, create new scenarios, and implement new action plans in what is becoming a hyper-commercial environment. Time Warner’s Walter Isaacson captured the significance of the shift in the capitalist organization when he observed that “the old establishment was a club, The new establishment is a network”.

Source = The age of Access, page 23.

A look at what I believe the X space should look like.

X is the academic space of tomorrow. The primary purpose of this space is to expedite the networked infrastructure necessary for knowledge fusion. In this space there are no walls, and there are no top down committees. This space is completely fluid, and in being so it is able to support the movement back and forth along the “order-to-chaos” continuum. The X space has safe guards against beurocratic policy. The x space has a political structure that purposefully subverts power playing. In the x space, power is simply looked down upon. The x space publishes to the general public, as well as to it’s academic peers. The x space has no titles, no tenure, and no rigid classifications of any kind.

Proposal Framework

Hi folks

Here is the first draft of our proposal that has since been adjusted, edited and changed.

In 2002, The BC liberal government passed legislation to dissolve the entity formally known as Tech BC and have SFU take over the programs that were offered there. Over the last few months the task of integrating three new departments (IT, IA, M&T) into the SFU fold, has fostered a discourse around the role of structure in academic institutions. Many ardently oppose the adoption of SFU’s established structure, arguing that the universities current approach to classifying academic departments serves little purpose outside of maintaining formal hierarchies, and clear divisions of authority. This argument goes on to point out that SFU’s structured, rigid approach to managing different knowledge domains is indicative of a modernist approach to higher learning that is simply no longer relevant to our contemporary social and cultural needs.
What’s clear to those who champion change over convention is that advances in today’s world require a convergence of knowledge across many disciplines. For this reason, meaningful research and innovation cannot, and will not move forward unless we make a concerted effort to promote and maintain collaborative relationships and knowledge synergies. The critical bottle-necks of the information age are no longer about transmission speed and processing power, but rather the ineffective sharing of information and skills across multiple knowledge disciplines.
Unfortunately, the bureaucrats, and academic politicians have become so caught up in their fight to maintain power that they fail to see how their inability to accept change could potentially contribute to the stifling of social and cultural evolution.
The primary goal of this work is to address that issue—that is, the importance of embracing new approaches to learning so that social and cultural evolution can be expedited in as efficient a manner as possible. This work aims to provide insight into the value and importance of side stepping convention at this critical point in history To achieve we plan on applying what some might call a literal adaptation of Marshall Macluhan’s famous statement “looking forward through the rear view mirror”
We plan to articulate our argument by forecasting the future in a compare and contrast type manner. To achieve this we will place our selves in the future, some (still to be defined) years from today, and report back on the current state of human experience. Our reports will compare and contrast two distinct perspectives. The first perspective will be based on the assumption that we have not embraced change well at this critical point in history, and that instead we have relied on established social, political, and cultural conventions to guide us as we evolve. Here we will make specific attempts to forecast what our experience might be like if we do not take proactive measures to improve knowledge sharing through out society. The second position will be in direct contrast to the first, and will essentially report back with the assumption being that we have embraced change that at this critical evolutionary juncture established convention has been forsaken in place of experimental thought and ideas.

Looking forward through the rear view mirror”.

Here are some thoughts about my blog, blogging, and collaborative knowledge sharing at Tech BC/SFU.

Warning, some of these thoughts may not sit well with everyone. If you are the type of student who spends most of your time listening and less contributing you might want to click the back button. Then again, maybe you should stick around, so that my sentiments are at least reaching the audience I intended this for.

Anyrate, this reflecting back on my weblog over the last ten weeks, has really ended up being an exercise in what did and did not work for me in this course. What I realized is that this web loging is, on a lot of levels, NOT my preferred approach to knowledge sharing. Finding the time to sit down, collect my thoughts, and compose a piece of writing for other students to read has become an activity that is simply low on my priority list. Some might say that this is selfish, or that I need to manage my time better, and I certainly would agree; I think we all could follow that advice on some level—the time management advice, that is. The reality for me however, is that I don’t think my finding-the-time-to-blog issue is simply a matter of poor time management. I personally feel that time, as an experience, is a manifestation of our choices in life. A person’s lifestyle will dictate their experience, and, indeed, this is the case with my inability to find the time to sit in front of my computer and blog.

The time we have in our days is finite. 24 hours minus 8 for sleep, 2 hours for eating, etc etc. I could break this down more but I think we all understand the point—to many things to do, not enough time to do it in. So, with this being the reality, we find ourselves in a situation where we are forced to prioritize our day-to-day activities. Those activities that we value, for whatever reason, get priority over others. In short, our individual valuation process plays an extremely important role in the way in which we manage our time.

Anyways, lets get back to the issue of my blog being a hassle, and why. In reflecting back, it seems I didn’t make the time to create a more meaningful blog because I simply didn’t value that activity as a worthy use of my time. So the question becomes, why didn’t I value it? Well, one reason is, I had a hard time finding the motivation to contribute to a collective knowledge sharing process where less then thirty percent of the group seems to want to contribute or has anything meaningful to say. As brutal as that sounds, it is in fact the way I feel. I have sat through countless hours of critiques and online conferences where myself and a handful of other students are the only ones contributing anything of value to the process. This school is supposed to be about interdisciplinary knowledge sharing, collaboration, and teamwork, yet the majority of the group that I study with chooses to be silent during collaborative knowledge sessions—both in person, and online. Frankly, I’m totally fed up with it, and I have a great deal of trouble spending my valuable time contributing to a culture that makes that kind of behavior OK. I’ve been through close to four years of teamwork and sat through countless session of critiquing other students work. I’ve contributed hours of my personal time to other students education and my experience has been that 80% of those students take, and do not return the favor. In my mind, these students should either contribute or move on. Go get a job at Home Depot, or the video store, or what ever. This is the fourth year of an academic program based on collaboration, and yet we still spend our time babysitting a group of comatose sponges who sit at the back of the room, in their safe little groups and stare at the carpet. Now I realize that my contribution style is different, and that not everyone values the same approach. I’ll also be the first to admit that I’m bit of a loud mouth, and maybe I say too much sometimes, but at least I contribute.

Now some might be thinking, “but Dale, you just finished saying you haven’t been contributing”. Well, in fact I have been contributing, but I have been doing so only out of necessity, and on the whole that process has been a bit of a hassle. That said, I suppose the purpose of this rant is to explain how I feel so that I can then put it away and move forward. If we are going to look back and learn something from our actions we need to be able to figure out the problem, deal with it in whatever way we need to, and then come up with a solution so that it won’t happen again. For this reason, I am all for putting my two cents into defining what the so-called school of “X” might be in the future.

So anyways, yeah…writing about my ideas and thoughts in an open forum is just not something I’m interested in doing unless I feel the time spent doing so is worthwhile. Over the last three and a half years my experience has proven that this sort of activity at Tech BC/SFU does not work for me, and is not beneficial to my educational goals. The time I spend partaking in this kind of activity is simply better spent doing other things—chopping wood comes to mind. Now I know that this course is about examining and exploring electronic culture and that this entails the collective contribution to a common experience. I also realize that we live, and go to school in a multicultural environment and the reality is that we have a melting pot of values and cultural norms to negotiate as a result. Don’t get me wrong, I respect and understand the elements of our design problem here.

That said, I am not proposing to just throw up my hands and no longer contribute to the collaborative process we are applying in this course, or degree for that matter. In fact, I plan to actively participate in the coming module, but I will do so more as a designer trying to solve problems and less so as a writer discussing them. I personally think there are more efficient approaches to expediting the sharing of knowledge in our ever evolving networked environment. I appreciate the value of reading and writing; however, I also understand that our social experience is evolving in increasingly complex ways. The devices and technologies we will use in the future may not be conducive to these more traditional forms of communication. I intend to use this consideration as my research platform for the coming module, and plan to investigate more efficient platforms for collaborative knowledge sharing using a ten years down the road perspective.

Testing the powerlaw hypothesis

Ok, so we've had some discussion around the nature of the internet and other networks, and we came up with this idea that when it comes to the web there are all kinds of power law distributions going on.

In the spirit of exploration (and getting the assigment done) I decided to use the google link tool to experiement with the Dr. Barabasi hypothesis that links on web pages will follow a power law distribution pattern, and that this pattern is in fact scale free. To this end, I decided to follow in the footsteps of my classmate and fellow powerlaw investigator/exposer, Hector Larious. Hector did a fantastic job outlining the a powerlaw experiment which focused on link patterns and News sites. In an effort to explore this phenomenon myself, and to also contribute Hectors work in some meaningful manner, I've decided to do a similar experiment but on a different scale. To achieve this difference in scale I chose to look at a more specialized topic set. Given that my blog is focused on design, and specifically experience design, I decided to experiment with 14 random links from my experience design favorites list. Again, I decided to do this using the google link tool. Below are the sites and their respective link values, as determined by the google tool. Below those values is a graphical representation which, indeed, indicates that a power law distribution exists. Unfortunately the scale diference I had would show up has not in fact done so. Interestingly, my data follows hectors quite closely, even though our site types where completely different.

The values

Adobe.com 118,000
Macromedia.com 46,000
Apple.com 14,300
Corel.com 7,520
Useit.com 6,790
AIGA.com 2,320
Puma.com 1840
Razorfish.com 1060
Sapient.com 1040
IIT 840
Nathan.com 782
Plumbdesign.com 488
Raremedium.com 444
Interaction-ivrea.it 384
Aiga-experience design 194
Electronicink.com 190

The graph


Cheers, Dale

The Eye Candy perspective

In the spirit of the coming Carnival celebration (Halloween) I’ve decided that some serious candy handouts are in order. Eye candy, BABY. We’ve done a lot of talking about Internet topology lately, so I thought these fancy little candy coated numbers were relevant.

Check out the clusters on these baby’s …..WHEN you click the image to get the animation make sure you give it a bit of time to download onto your machine..

This graph visualization shows the topology of the core of the Internet from mid-January 2000. It reveals the peering relations and geographic locations of Autonomous Systems (ASes), which are a vital part of Internet infrastructure that represent large ISP networks for the complex routing of traffic flows. It was created by researchers at CAIDA as part of their skitter project.


This image is taken from one of three cyberspace visualization sequences in the William Gibson scripted film Johnny Mnemonic.

This map compares the geographic distribution of Internet routers (top) against the global distribution of population (bottom). It was produced by Soon-Hyung Yook, Hawoong Jeong, and Albert-Laszlo Barabasi at the University of Notre Dame as part of their research in the network structure of the Internet. For more information see their paper, Modeling the Internet's large scale topology

This map is a PDF of the core anatomy of a linux system. Extremely fantabulous, and very cool.

Finally, and very much in the Spirit of Halloween, comes this last piece of extra special eye candy. This dark and interesting film called Warriors of the Net is a must see perspective on the workings of the Internet. Here is what others had to say:

“The Internet is imagined, and made tangible, on the movie screen, as a dank and grimy place, reminiscent of industrial factories from the nineteenth century. Warriors of the Net is not the slick, clean-room cyberspace of solid state electronics and fibre-optics, but a dirty, mechanical otherworld of clanking machines of riveted steel, levers, armatures and elevators. This is perhaps a Victorian Internet [2]. As Elam told Map of the Month in a recent email interview, “ the way routers and firewalls work seems to me a lot like old time factories. Picking up something here, dropping it there. Nothing really new there, very mechanical. I had rough and mechanical and went from there, trying to add some of the popular aesthetics from the net culture ... the dark, moody space etc.”

Source:

Note the source for much of what I've posted here is the Atlas of Cyberspaces. Be sure to check it out for more wonderful candy coated Internet visualizations.

Happy Halloween

Understanding the scale free power law deal

So, this week we learned about the power law characteristics of the Web. According to the experts, when it comes to the web there are all kinds of power law distributions going on. For instance there are many poorly connected sites, and only a few that are well connected. Also, when it comes to user patterns, the mass of users tend to flock to a few select sites, while the remaining sites tend to get ignored. These characteristics are in keeping with what is known as a power law, which in mathematical terms means that
“the probability of attaining a certain size x is inversely proportional to x to some power, whose numerical value is greater or equal to 1.”

The reason that power laws are interesting is that unlike the more familiar bell-shaped Gaussian distribution, a power law distribution has no 'typical' scale and is hence frequently called 'scale-free'. Hector does a nice job comparing the difference between a normal distribution and a power law distribution. Check out his nice work here.
We are all familiar with the bell curve and its use as a grades distribution map in academics. The apparent logic here is that in any sample of students there always seems to be a characteristic grade spread that represents the majority. So in a class of 30, the majority, say 20 students, will be average, while 5 might be above average and the other 5 below. When plotted out on a graph, this pattern represents a bell shape with the grade spread majority defining the peak of the bell. This bell peak with lows on each side is the nature of a Gaussian, or normal distribution. The difference between a power law and a Gaussian distribution is that in the power law graph there is no peak, the pattern simply starts high and then tappers off slowly (again take a look at Hectors two graphs to see this represented visually). Research has shown that this kind of distribution occurs frequently on the world-wide-web. For instance, if we dealt with a distribution of sites that had between one and 100 links, we would see that the number of sites that present with one link is the highest and that as we move towards sites with 100 links this representation simply shrinks. There is no standard value for the number of links on a site, we do not have a graph with a peak, many sites have few links, and few sites have many. To understand the notion of scale free, all we need to do is point out that this power law distribution occurs regardless of the scale we negotiate. For instance, if one were to look at the distribution of site sizes, for one arbitrary range, say between 10,000 and 20,000 pages, that distribution would look the same as that for a different range, say between 10 to 100 pages. In other words, zooming in or out in the scale at which one studies the web, one keeps obtaining the same result, i.e. an inverse power law in the probability of finding a given feature.

My Small world network Map

In an effort to put knowledge into practice our assignment for the second week of Module two of electronic culture, was to create a diagram of a web based social network to which we are personally connected. Based on our working diagram, we were asked seek out and identify one distinct small network with in our chosen network.

The community:
The networked community I have chosen to highlight is the user experience design community—more specifically, user experience design sites that are linked to the AIGA. My involvement with this community is an outgrowth of my academic studies, my research, and previous professional employment.

My method
My approach for finding a small network with in this community was as follows:

Step One: Performed a Google search with the following parameters:
AIGA + “User Experience Design”

Step Two: Recorded all the results, by name, URL, the time it took to download, and the number of images on each site.

Step Three: Searched for sites that were blogs—found 7.

Step Four: Search all seven blogs to see if I could find links between them, as well as my own personal blogg.

Step Five: Created map of results.

The following map presents a small world network of blog sites that are user experience design related, and have some affiliation with the AIGA. The blog sites found via my Google search are orange ovals (these are hyperlinked). The other sites I found on that Google search are represented by the blank orange ovals. The hexagons (these are hyperlinked as well) on the map represent links from my blog site that are in some way related to small world topic.

Note: Almost all blog sites are linked to each other in less then six steps. Also of interest is the fact that my involvement to the community is one-dimensional. I found no links to my blog, only links from me to other sites.

See the map here

My Small world network Map

In an effort to put knowledge into practice our assignment for the second week of Module two of electronic culture, was to create a diagram of a web based social network to which we are personally connected. Based on our working diagram, we were asked seek out and identify one distinct small network with in our chosen network.

The community:
The networked community I have chosen to highlight is the user experience design community—more specifically, user experience design sites that are linked to the AIGA. My involvement with this community is an outgrowth of my academic studies, my research, and previous professional employment.

My method
My approach for finding a small network with in this community was as follows:

Step One: Performed a Google search with the following parameters:
AIGA + “User Experience Design”

Step Two: Recorded all the results, by name, URL, the time it took to download, and the number of images on each site.

Step Three: Searched for sites that were blogs—found 7.

Step Four: Search all seven blogs to see if I could find links between them, as well as my own personal blogg.

Step Five: Created map of results.

The following map presents a small world network of blog sites that are user experience design related, and have some affiliation with the AIGA. The blog sites found via my Google search are orange ovals (these are hyperlinked). The other sites I found on that Google search are represented by the blank orange ovals. The hexagons (these are hyperlinked as well) on the map represent links from my blog site that are in some way related to small world topic.

Note: Almost all blog sites are linked to each other in less then six steps. Also of interest is the fact that my involvement to the community is one-dimensional. I found no links to my blog, only links from me to other sites.

See the map here

Maverlous Networks collaborate part two

Ok, so last post I was talking about this research paper I came across that discussed the similarities in features of collaborative networks--see the post below this if you need a refresher. What really intrigued me about this research paper was how the authors proposed to investigate artificial social collaboration networks, and the results they produced that supported the notion that some underlying rule set is contributing to the may networks evolve. Basically, the paper proposes to investigate the structure of artificial collaborative networks by analyzing the Marvel Universe collaboration network, where two Marvel comic book characters are considered linked if they jointly appear in the same Marvel comic book..

"The Marvel Universe network captures the social structure of this Marvel Universe, because most pairs of characters that have jointly appeared in the same comic book have fought shoulder to shoulder, or each other, or have had some other strong relationship, like family ties or kidnapping. Thus, it shares, in its artificial way, the true social nature of scientific collaboration networks, while the way it has grown has echoes of the Hollywood network, as writers, directors and producers create their characters and assign them to actors in a way that somewhat resembles the way Marvel writers make characters appear in comic books. Thus, besides any sentimental or cultural motive, this is where the main reason for studying the properties of the Marvel Universe lies: it is a purely artificial social network, whose nodes correspond to entities and whose links have been raised by a team of writers without any preconception for a period of forty years. "

The research paper analysis of the Marvel network is based on a set of database numbers that archives the collaboration numbers associated with the comic books over a forty year period—for example, the number of characters (6486), the number of books (12942), mean books per character (14.9), mean characters per book (7.47) so on and so forth. The research outlined in the paper goes into an in-depth statistical analysis that is understood when considered in the paper itself. The scope of this analysis is simply beyond the scope of this post so I wont go into particulars.

Instead, for the sake of brevity, I thought it best to simply skip right to the outcomes of the research. In order to get your head around the outcomes we do however, need to understand the way these outcomes are measured and expressed—to this end we need to understand a metric known as the cluster coefficient.

Lets first refresh the small world network paradigm. In most social networks, two nodes that are linked to a third one have a higher probability to be linked between them: two acquaintances of a given person probably know each other.

This small world effect can be measured using a (statistical value known as the) clustering coefficient. The clustering coefficient measures the fraction of the neighbors of node “V” that are linked.

Getting back to our comic book paper, lets first note that paper written to be in dialogue with other network research--research that looked at the characteristics of real social collaborative networks and how they related to random collaborative networks. In short, the relevant findings of this research, is that real life collaboration networks have a clustering coefficient roughly twice the one of their null random model.
Some normal collaborative networks and their cluster coefficients are:

Hollywood network (Kevin bacon style)- 0.199
Various Scientific networks – between .3 and .8

Moving right along, the Marvel research showed the following:

The Marvel Network (with 6486 nodes and 168 267 links)—0.012
A statistically determined null Random Network (with 6486 nodes and 168 267 links)—0.0066

What is interesting about this is that similar to the true social collaborative network, the artifical network had a clustering coefficient that was twice its null model.

So the insight is as follows.

The final structure of any actual collaboration network, be it real-life or artificial, differs from its null random collaboration network model roughly in the same way, and thus insight is that there is probably a common mechanism that produces them.

Cool eh.

Dale

The Marvel Paper

You can find the Marvel Comic artificial network research paper discussed in the preivous and coming post at this link:

Marvel Research Paper

New considerations for Social networks

So to pick up where we were last post, we were discussing the similarities between social networks and computer networks. This post I’d like to discuss similarities again but in a somewhat different manner. I’d like to discuss similarities between a particular type of social network known as the collaborative network. This seems relevant for a number of reasons. First, I think such a discussion is important given our current efforts in building an online collaboration platform. Second I find this notion of network collaboration compelling from an interaction design stand-point. Third, I found this really cool white paper that talks about some really cool characteristics associated with collaborative networks and I’d like to share that with as many readers as possible.

We spoke of a well-known collaborative network last post when we discussed Kevin bacon and the Hollywood actors network he is currently the poster boy for. Another common collaborative network we looked at in our readings was the Scientific collaboration network. “In such a network, nodes represent scientists and links denote the co-authorship of a scientific piece of work contained in some database.” One example we looked at was the network associated with Paul Erdos who was a Hungarian mathematician who published over 1500 papers with 492 coauthors, more than any other mathematician in history. A little poking around revealed that other scientific disciplines have been studied along this line as well. Researchers have looked at databases in neuroscience, high-energy physics, and biomedical sciences. So far the outcome of these investigations is that all of these social collaboration networks seem to exhibit patterns in keeping with the small world phenomenon. These insights have become the impetus for more investigation, and as more and more examples of small world patterns surface researchers are finding it hard not to ask certain questions. One such question that is being asked is as follows:

“Does this similarity in features (here they are referring to small world features in collaborative networks) represent some profound principle in human interaction? Or, on the contrary, does any large network with some collaboration between nodes present these characteristics?”

This particular quote comes from the white paper I mentioned in my opening paragraph, and if I haven’t intrigued you yet I’ll probably grab you soon enough. What’s even cooler about this white paper is the way in which they go about investigating a potential answer to their question. First they set up their ideas by distinguishing between different social network types. To this end the authors speak of the difference between a true social network and one that is forced or less natural.

“Newman argues that scientific collaboration networks are true social networks, since most pairs of scientists that have written a paper together are genuinely acquainted with one another. The social meaning of the Hollywood network is, in this sense, weaker, because it has been built up mainly through the decisions of cast directors, producers and agents, rather than voluntary collaboration of actors.”
I thought this was an interesting insight. If we want to discuss network collaboration in a social sense It’s certainly worthwhile establishing the boundaries and benchmarks. The falsity of the Hollywood collaboration network is something I hadn’t considered up until I read this paper. It’s certainly got me think though. I wonder what sort of social network we have in our meta blogg? Could we say it was a natural collaboration network? I mean, I would certainly consider everyone in our group an acquaintance, but I doubt whether I would be collaborating online like this if it wasn’t required by the course. This is an interesting consideration with regard to our task of designing our own network. Are we here collaborating in a natural sense, or is Laura just the director of some production that requires our input? I’m not going to answer this question cause I think it’s a bit dangerous. All the same I think its compelling and a possible seed for an interesting discourse.

Look for part B of this post coming soon.