available at http://code.google.com/apis/chart/

Today i travel to Brussls and I’ll be [there]

We wrote an article for the book “Learning Communities. Das Internet als neuer Lern- und Wissensraum” published by Christina Schachtner, Angelika Höber at Campus. More info about the book can be found at Campus and Amazon.

Our contribution about “Visualising information flows in self organising knowledge networks” and can be found [here]. (in German)

Many Eyes is an easy to use data visualisation tool. First you upload data in the form of a spreadsheet, then you define forms of visualisations and finally customise and publish it. Many Eyes offer a dozen different visualisation types (maps, graphs, charts, histograms, and even network diagrams) and it is possible to apply a multitude of different forms to the same data set; Thus it is possible to play around with figures and to discover and highlight different aspects within the same data set. It is easy to integrate a thumbnail of a visualisation in your blog that links to the correspondent page at Many Eyes.
A thumbnail is by definition not rich in details and therefore you need to click on it in order to see the actual information. In the first moment one might prefer having the actual visualisation in the own weblog, but Many Eyes is not a mere visualisation platform but also a forum for interpretation. People start to discuss data like in this case. And that’s actually the greatest benefit of the service. It combines state of the art visualisation with the blessings of the living web.
I doubt that the masses will start discussing data sets but I think there’s a general tendency to explore global interdependencies. In a “globalised world” figures seem to be the most concrete evidence for developments, because in most cases we don’t have a first hand experience. Therefore statistics and network analysis seem to be an appropriate and necessary means of developing new forms of perception and discourse in order to cope with actually invisible but nevertheless vital challenges. I hope that XXx and XXX will go in with their approach.

http://services.alphaworks.ibm.com/manyeyes/view/S2fqLEsOtha64-EgR_rLE2-

Thanks Dietmar Offenhuber and Gerhard Dirmoser from SemaSpace for sending me the link to Many Eyes!

This is the kind of democracy we would really need: First present the facts, Second discuss it in all aspects. And third make a decision on it.

By this summer two applications, using Facebooks API, have launched. They can be seen as the first field test of social network analysis within a broader audience of non-technical users. Apart from the actual design of the applcation, the reactions of the users, often being in first contact with social network analysis are interesting lessons to learn.

Design: First of all one has to state that both TouchGraph (TG) and the Interactive Friends Graph (IFG) seem to be largely inspired by Danah Boyd’s and Jeffrey Heer’s prototype Vizster. That’s not a critic, as vizster was a proper design addressing most of the questions a user might ask her/himself when browsing her/his social network. It’s wise to reuse design that has proven itself. Clustering and displaying common friends are logical usecases that have been already covered by Vizster.
The limited number of use cases – especially for non-scientific users – and the grammar of network graphs defined by nodes, edges and proven layout algorithm make it almost impossible to reinvent the wheel. So to a certain extent network graphs cannot avoid looking similar and using a common language.

Common problems: Both Applications suffer to a large extent from the fact that profile informations are largely not public within facebook. Even if your friends allow you to see their friends, connections between them easily disappear, as the path simply ends when a user’s profile is hidden. The Interactive Friends Graph tries to overcome this problem by some sort of viral marketing strategy: It has a special function to invite friends to publish their friendship relations in the form of the IFG. This may work out to a certain extent but nevertheless it remains a barrier for a user that want to explore a persons network. Touchgraph tries to solve the problem with another trick: It takes advantage of photo tagging what allows you to display networks of people tagged on the same photo.
“One can not see another person’s whole social network because Facebook only allows applications to get a list of one’s own friends. For other users it is only possible to get a list of people that they appear in photos with. Perhaps Facebook’s policy will change in the future.”

If you are lucky by having a large Facebook network of friends then Touchgrouph provides a wonderful tool to explore all the connections between your friends.

Metrics: The policy of ‘Facebook makes sense because it protects people from being stalked but it has negative impacts to the application of metrics. One must consider that the probability of being cut off raises exponentially with each degree of separation from a central point, simply because of the fact that the connecting point might not be within your network.
“Once one has launched the application, one can explore one’s extended social network by loading more photos for friends. Loading photos will add new users who are tagged in photos to the graph, and created edges between them based on friendships and common photo appearances. Note: It is only possible to load photos for friends and people within one’s network.”
Its simply ridiculous that facebook applies the term network to people of the same nationality or the same university and provides far more information for people within than for people outside of one’s network. There’s a structural barrier for becoming friends with people outside your own network and therefore any metrics will only affirm these restrictions.

Or lets put it in other words: The ways how blogs link in the blogosphere is far more inpredictable, because its easier to escape from national and other social ties whereas facebook structurally supports friendship connections within the own neighbourhood. One of the main benefits of network graphs seems to lie in providing a tool to go beyond your own neighbourhood and taking advantage of a weak tie between an important actor and yourself.
Within Facebook such explorations are rather hindered than supported.

Nevertheless the Touchgraph Facebook Photo Browser is certaily among the best WORKING social network analysis tool currently available for online usage. It has variety of fascinating and usefull features and is worth being tried out - if you have large facebook network.

Einladung zur zweiten deutschen Konferenz für Informationsarchitektur, die am 9. und 10. November 2007 unter dem Titel „Information Raum geben“ bei der Hochschule der Medien, Stuttgart (HdM) zu Gast ist. Die diesjährige Konferenz bildet gleichzeitig das Programm des 6. Symposiums für Informationsdesign und wird gemeinsam vom Studiengang Informationsdesign an der HdM und dem Institut für Informationsarchitektur veranstaltet.

mehr infos [hier]

Last Thursday we have been guests of Gerhard Dirmoser, who showed us his impressing collection of diagrams and his diagrammatic library. Gerhard is one of the leading experts in the field of diagrammatic and is devoting his work to the development of a new epistemological approach to describe and order diagrams. This approach is outstanding, because it aims to work finally without textual description, only on diagrammatic relations. Therefore probably the word “description” is inappropriate at all, because in Gerhards studio you realize that his research process consists in ordering, relating and placing objects, very similar to Aby Warburgs Mnemosyne. (see also german wikepedia entry on Warburg)
Aby Warburg revolutionised art history by introducing replications for didactic purposes. Nowadays image processing and graph engines can produce new experiences of exploring art. Gerhard Dirmosers and Dietmar Offenhuber project SemaSpace is exactly about the question of exploring semantically structured data and memory spaces. Dietmar Offenhuber convincingly solved the problem of handling large amounts of nodes, even several thousands – and even if the nodes are represented by images. Here’s a short description of SemaSpace by the authors:

SemaSpace is a fast and easy to use graph editor for large knowledge networks, specially designed for the application in non technical sciences and the arts. It creates interactive graph layouts in 2d and 3d by means of a flexible algorithm. The system is powerful enough for the calculation of complex networks and can incorporate additional data such as images, sounds and full texts.

On the SemaSpace Website you will find not only the tool but also an interesting application:

“25 years of ars electronica
study conducted by Gerhard Dirmoser, contains all projects / people involved in ars electronica until 2003, based on collected material and data from the ars electronica database. original files of the study:”

But SemaSpace is more than an organised database. It represents a “space of memory” that commemorates the threads of theory and media art within the “ars electronica universum.” It can be seen in the tradition Giulio Camillos Memory Theatre (see also http://www.clausmoser.com/?p=378) (By the way Camillo is a must for interaction designers)

Dietmar is currently working on a new version of SemaSpace and Gerhard is now about to network his collection of 4000 diagrams within the graph editor. As already two thirds of the work has been done within 20 workdays it is quite obvious that it seems an appropriate way to organise large amount of image data in a reasonable time span.

There’s a lot of other work (texts, diagrams and network graphs) by Gerhard available here: http://www.servus.at/kontext/ARS/ (strongly recommended).

Special hint for us lucky Austrians: next Sunday, February 4, a whole day lecture takes place at Audi Max of Danube University Krems.

Here are some remarks on BuzzFeed after having tested it for some days.
First of all, it does what it promises: It feeds you with buzz.
The term buzz itself implies that there is a greater audience behind. It will not easily become a buzz when two mathematicians are discussing problems in algebra. Buzz needs a bigger number of people that talk about it and a potential to infect even more people. A buzz from the last year is no longer a buzz. BuzzFeed detects buzz before it becomes a bigger thing.

BuzzFeed is showing buzz a few moments before its tipping point. From an analytical perspective it is already clear that a new buzz is emerging, but the masses don’t know it yet. BuzzFeed is therefore an adequate means of keeping up with the public opinion and to be some eye glimpses ahead. It’s an accelerator of public discourse. But do we really need even more accelerators? Tools like BuzzFeed make it very clear that the blogosphere is a huge discourse machine and that its speed and effectiveness is growing. The whole machinery is based on the simple fact that communication is producing communication; sometimes a cascade of communication; But what is the outcome of it? Doesn’t that lead to a more and more superficial mode of communication? Does it make us more fit to face the challenges of a crazy and complex world or is it just another step to make it a bit more crazy and complex? To be honest I don’t know.

Under the bottom line – and beyond all sociological considerations (sorry I couldn’t withstand) - BuzzFeed is simply an vanguard media. It typically combines the following components:
1. Consumer Generated Media - mainly weblogs – that provide ever new content; in this case CGM is working like an armada of journalists chasing for latest news. Or to put it in other words: they work like sensor neurons in our nervous system that fire when they perceive a stimulus.
2. Analytical tools detect trends within the blogosphere. In the case of BuzzFeed these tools detect upcoming topics as patterns. Patterns mean that there’s not a chaotic sequence of “firing neurons” but there’s something going on; something that needs further interpretation.
3. Obviously these patterns are not self-explaining and require some training to interpret them. Therefore BuzzFeed hire editors to separate the wheat from the chaff and to write short introductory texts to topics they consider being upcoming and interesting enough to get featured.

BuzzFeed is therefore a hybrid media that combines a very large network of writers, computational power and human judgement. The latter seems not to be replaceable by technology and is still the key factor that makes a project juicy. We may expect many more interesting combinations of theses three components that make up new web media formats, not only including text but also podcasts and video.

In the past much more effort has been spent on visualising email conversation than visualising blog diffusion. Though it’s a different domain blog analysis can learn a lot from work previous work done in the field of email archives.
In both domains there are huge archives that reflect our interests and conversations with others. Default functionality like ordering archives by time or author and search functionalities are proper means for finding information, but there’s almost no functionality for browsing archives in order to explore personal developments, the cyclical up and down of interests or the path of conversation between two persons.

In the following I refer to a paper by Judith Donath, Fernanda B. Viégas, and Scott Golder “Visualizing Email Content: Portraying Relationships from Conversational Histories” in which they present a prototype called “Themail”. It is based on Salton’s TFIDF algorithm which compares the frequency of a certain word in a limited time span (e.g. a month) to its frequency in the whole archive. If there’s a relative high frequency it is displayed in a larger font in order to highlight its importance. This technique was used to analyse the email communication between the owner of the mail archive and a specific conversation partner over a series of months (see Figure 1). User testing, done by the authors, demonstrated that this form of analysis shows good results in characterising developments in the personal relationship and helps in assigning hot topics to specific months. E.g. in email conversations before a wedding, words like “invitation”, “tables”; “drinks” and guests names were used more frequent. Or a travel to Asia resulted in words like “Bangkok,” “thai” and “kuala”.

Figure 2 shows that after the return the conversation turned back to programming and other usual themes of conversation. Users like to explore their archive together with friends and conversation partners, because it tells a lot about the evolution of a relationship (like from classmates to lovers)

Similar analysis could be done for Weblogs; either for characterising the archive as a whole or single months or categories. Word frequencies of a weblog could be compared to overall frequencies in the blogosphere and could be output in word lists which describe the blog’s content. Phrases would do even a better job than single words. A system like Amazon’s SIPs (statistically improbable phrases) could probably describe a blog’s content more “objectively” that a tag cloud based on the author’s personal tagging. A similar idea has been posted by Rageboy (see also David Weinberger.)

Judith Donath, elaborated the Themail concept a step further. She mapped the email conversation between six researchers over a period of 22 days. The conversation took place in preparation of Janet Abram’s and Peter Hall’s book “else/where: mapping” (Donath called her prototype “The Rhythm of Salience” and it was published in the same book.) On the x-axis she distributed the names of the researchers; the y-axis mapped the flow of time. In the whole conversation only 30 messages were exchanged; They are displayed as full text. Visualisation aims to map temporal rhythms and the patterns of interaction between the participants. Each message is represented by a white square; thin white lines between the squares show the reply structure. Important words and phrases are highlighted in a similar manner like in Themail.

As in the case of Themail the usefulness of the map depends on the user’s relation to the mapped conversation. I’m quite sure that it is very useful for the people involved but for outsiders it provides only superficial information and is only useful in a bigger size and when printed out, in order to read the details. I also doubt that the length of the messages allow for reliable content analysis like SIP, in order to highlight important phrases. – The map was handmade and highlights were made by personal estimate. Nevertheless it is an interesting approach to map information diffusion and interaction; probably also useful for the blogosphere. It’s quite obvious that in such a map only a smaller number of messages can be displayed. For a bigger number of messages other forms of visualisations – like e.g. animated maps - might do a better job.

further information:
Rhythms of Social Interaction: Messaging within a Massive Online Network
Sociologically Improbable Phrases

An cool way to explore html-code is the htmlgraph (Websites as Graph).
It is written in processing and traer.physics which is a particle system physics engine for processing.