New book

I received a book yesterday, finally. I had ordered John Urry's Global Complexity over a month ago, but it was out of print for a short time. I had to wait for them to print me up a fresh copy, I guess. I'm excited since it's exactly the perspective I'm looking for on international interaction.

Often before I read a book I like to read the comments that other people write about it on Amazon or other sites. I usually read the comments from those who rated the book low as they often have the most striking opinions. The lowest comment from this book is:

Urry seemed to condense what should have been 600 pages into 150. And they were some of the hardest 150 pages I've read. Complexity theory is a fascinating topic and its application to globalization is definitely relevant. However, I found Urry very difficult to follow and I was left unconvinced. I would strongly suggest reading M. Mitchell Waldrop's book "Complexity" to get a much clearer perspective on the theory.

He notes that the book is dense as though that were a problem. I prefer dense books. Just give me the idea so I can mull it over. I don't need the author to do all the thinking for me. If Urry had expanded this book to 600 pages I probably wouldn't read it.

I'm a slow reader. Not because my actual reading speed is slow, but because I often stumble on an interesting idea while reading and trail off into thought. I prefer if the reading is dense so that it can accommodate my flights. All else is fluff. With books like Waldrop's* I find myself quickly bored and skimming for the next interesting part. Urry's book seems densely interesting. Looking forward to it.

* - Although that book is actually very interesting - there are better examples for what I'm talking about.

Do you enjoy looking at graphs?

I saw a graph made from age distribution data from the Census Bureau at Economist's View. It's a pretty cool chart. Except for the fact that the default Excel coloring and labellings are uglier than sin.



Excel has some incredible visualization capabilities if you know how to use them. I thought that such interesting presentation of interesting data should not go to waste so I produced my own version also in Excel:



It's like geological strata on the side of the highway.

Free downloadable book on computational modeling

It's mighty scant at this point, but it includes plenty of problems for people who might want to challenge themselves and improve their understanding of the topics. And it's at Version 0.0.10... it has a ways to go. It's all done in Python too, for anyone who might be interested in Python.

I'd probably do everything in R though.

Its the simple things

vs.



I found it really difficult to tell when the trend was negative or positive without a good 0-line. Also, you probably only have to label every few month labels, like Jan., Apr., July., Oct. - the current axis makes everything all crowded.

Via Traffic

On Amazon, other people can't see your shopping cart

This reminds me of the parable of beer and diapers. I guess moms need more than just a rest break.

Reading list on complex networks

Apparently there's a reading group in Santa Fe on complex networks. The list provided is excellent.

This one looked interesting:

Aguirre, B. E., Quarantelli, E. L. and Mendoza, J. L. The collective behavior of fads: the characteristics, effects, and career of streaking. American Sociological Review 53, 569-584 (1988).

Evolution of the bio-tech industry

Herein are slides on the development of the bio-tech industry. I honestly can't recall where I found the link to this, but I like topic. The best part is it uses bipartite networks and doesn't collapse the different classes of nodes and studies them in the raw.

The interesting part about the dynamics of this network is that it grows and grows until it hits a capacity some time in 1992. The authors find a power-law distribution in the number of links, which is pretty typical for such networks. And then the vogue thing to do with dynamic networks with power-law distributions is to look at the change in 'alpha' over time. There's not a lot to gain from the slides though, I'm interested in the paper this might go along with.

So I found Powell's website and found this paper on Network Dynamics and Field Evolution. It seems similar, but not exactly. Anywho - it's a good example of anlysis of a dynamic two-mode network.

Trends in cognitive science: sociology

Computational Models of Collective Behavior

From the conclusion:

Cognitive scientists often act as though individuals are the sole loci of organized thought, but ABMs remind us that organized behavior can be described at multiple levels, and that our thoughts both depend upon and determine the social structures that contain us as elements within those structures.