The Big Duh Self-Portrait

This past week I painted my first self-portrait. My brilliant nephew, Kevin Rusnak, took the photo of me at a family barbecue.

I decided to call this painting The Big Duh Self-Portrait, in homage to Chuck Close's Big Self-Portrait and to Richard Avedon--two of my favorite artists. Despite all my interest in complexity, I am ultimately drawn to the human face and portrait. Painting this picture was a lot of fun--albeit a bit weird, as I have never painted myself before. As you also can see, I very much enjoy self-deprecating humor--not something as widely celebrated in highbrow art as it should.

Here is a SLIDE SHOW of the portrait as I worked on it.


cartoon comics complexity -- or, one big mob

I have always been a huge comics fan. I wasn't so much into the superhero genre, though. I was drawn more to humor, social critique and science-fiction comics. In particular, I was a huge fan of MAD Magazine. My specific heroes were Don Martin, Sergio Aragon├ęs, and those drawing during the 1970s, early 1980s.

For some reason, I have always treated comics as something worthy of the canvas. As such, for years, I have been painting, as well as drawing, comic characters. Most of my work aims at creating complex forms. My inspiration comes from complexity science--in particular, fractals, chaos theory, and dynamical systems--and, in terms of art, the complex forms created by many Asian wood and ivory carvings, and by the various battle and group scenes sculpted, carved or painted during the Renaissance. In fact, many of my cartoons are 3-D: i start with some backdrop (canvas, wood, foamcore board) upon which i glue various 3-D figures. it is very time consuming and tedious, but the result is very satisfying.

I call my cartoon complexity OneBigMob.

For more pictures, visit my website.

If you really dig these images, see my cartoon t-shirts at my Cafe Press store.


Pockets Full of Memories -- Complexity Art

On 1 Sept 2009 I posted on the "SOM for qualitative data" work done by Timo Honkela and colleagues at the Helsinki University of Technology. Exploring Timo Honkela's work further, I found out that he and his colleagues are also involved in the application of the SOM to the world of art.

They were involved (2003-2006) in an incredible interactive exhibition at the Centre Pompidou Museum of Modern Art in Paris.
Here is a brief description of the exhibition from the website--which you can visit by clicking here.

"Pockets Full of Memories" is an interactive installation that consists of a data collection station where the public takes a digital image of an object, adds descriptive keywords, and rates its properties using a touchscreen. The data accumulates through-out the length of the exhibition. The Kohonen self-organizing map algorithm is used to organize the data, moving the images of the objects into an ordered state according to similarities defined by the contributors’ semantic descriptions. The archive of objects is projected large-scale on the walls of the gallery space showing various visualizations such as the objects positioned in the 2D matrix, their movement over time, and textual descriptions. The audience can also interact with the data online to access descriptions of the objects and to contribute comments and messages to each object from anywhere in the world.


Grounded Neural Networking

If you are into neural nets, you know about the Laboratory of Computer and Information Science at the Helsinki University of Technology. One of the Department's most important professors is Teuvo Kohonen, the creator of the self-organizing map algorithm (SOM). The deparment also provides one of the best shareware downloads (SOM Toolbox) for using the SOM--it runs in the MatLab environment.

As I discussed in a previous blog (4/01/09), in 2003 I published an article in Symbolic Interaction exploring how qualitative researchers can use the SOM to conduct grounded theoretical investigations of large, complex, numerical databases. For the next six years, I sat around hoping someone other than myself would find the idea interesting and useful. Nothing happened! I know that publishing on mixed methods seldom goes anywhere, but I thought that, with the incredible advances taking place in complexity science and informatics and the internet, qualitative researchers would eventually consider the idea.

They have yet to do so. But, perhaps the latest article by Nina Janasik, Timo Honkela, and Henrik Bruun of the Helsinki University of Technology can change people's minds.

The title of their article is TEXT MINING IN QUALITATIVE RESEARCH. The purpose of the article is to show qualitative researchers how to apply the SOM to qualitative data.

Here is the abstract:

The article provides an introduction to and a demonstration of the self-organizing map (SOM) method for organizational researchers interested in the use of qualitative data. The SOM is a versatile quantitative method very commonly used across many disciplines to analyze large data sets. The outcome of the SOM analysis is a map in which entities are positioned according to similarity. The authors' argument is that text mining using the SOM is particularly effective in improving inference quality within qualitative research. SOM creates multiple well-grounded perspectives on the data and thus improves the quality of the concepts and categories used in the analysis.

When I read this article I was more than a little excited! I cannot tell you how much time I spent between 2001 and 2003 at the Helsinki website trying to learn about the SOM and figuring out how to use the SOM Toolbox. Let's just say it was a lot and leave it at that. I also cannot tell you how much respect I have for the researchers there. Incredible research; they make their work and software freely available to others. It is just fantastic.

I also have to say that Janasik, Honkela, and Bruun do an excellent job addressing the limitations of my 2003 article--in particular, how I did not go far enough in demonstrating just how useful the SOM is for qualitative work. As such, I agree completely with their critique. And, I agree that any qualitative researcher trying to figure out how to do their work in the digital age should read this article.

Enough said...

Key Words: grounded theory • constructivism • self-organizing map • text mining • document interpretation