Due to the generosity of various sponsors, the AHCNworkshop did not have a registration fee – but since the location was limited in size, participants were asked to register for a cost-free ticket. At the evening before the workshop I found out that I was 83rd on the waiting list for such a ticket! Nonetheless, I just went there next morning and was lucky that some of the registered participants had not shown up. But boy, they really missed something!
I had very high expectations towards this workshop since a similar one at the ECCS’10 (also organized by Maximilian Schich) had already been splendid – but all my expectations were met and even exceeded. The workshop took place in the very modern building of the Ludwig Muzeum, directly located at the Danube. Everything was splendidly and most generously organized: no fee, but an extraordinary good caterer with plenty of coffee and pogacsa supply (small Hungarian bread), and the most inspiring talks I heard on the whole conference. Do I sound enthusiastic? I definitely am! The broad field of topics, the enthusiasm of the many people which just started to explore the possibilities of network analysis for their field was just energizing. I’ll give you an overview of the topics and some of the (subjectively) most interesting points.
The first keyword was given by Marek Claassen, on how to automatically score artists. Of course, there is the obvious way by simply summing up the money paid for their works, but Claassen proposed a more detailed model in which fame and recognition are quantified. The main idea is that an exhibition, especially if it is a solo exhibition at a renowned institute, gives more attention to the user and that this is like a currency. Of course, such a talk rises a lot of questions and even emotions but it was an interesting start into a workshop which focuses exactly on this frontier: are we able to explore human culture by quantifying stochastical traces in our digital, virtual world?
Next, Tom Brughman showed his enthusiasm for using network analysis in archeology: he showed how he links various sites by the types of artifacts found at these sites. This research is still young and ít is not yet clear what kind of questions can be answered with it – which makes it all the more interesting for network analysists.
An absolute highlight was the keynote talk by Jean BaptisteMichel about Culturomics [1][2]. So, he and his co-authors wondered: Hey, within 10 years we can either read a few books very concentrated---or we could read 5 million books very superficial – let’s find out how much we can do with the latter! And they started to use 5 million digitized books from Google books which amounts to approximately 4% of all books ever published. In these books they looked for the probability that an irregular word becomes regularized, the time it takes until a new invention like the car, telephone or washing machines makes it into a book, or which profession is the most percepted and the one most persistently found in books. The result of the latter is clear: if you’re looking for fame you need to become a politician, but never a mathematician! I was very much astonished how far their approach took them – amazing talk. I’m sure we will hear more of him and his co-authors.
Even after this really great talk, the next invited speaker Natalie Henry Riche had absolutely no problem to switch our focus to a totally different but equally fascinating topic: visualization of large complex networks. She has developed different software tools which all look very interesting: in her PhD she tried out various ways to display graphs as adjacency matrices or to integrate adjacency matrices (e.g., of dense groups) with a ‘normal’ 2D-embedding of the graph. Within the adjacency matrix approach she, e.g., had the idea to fold parts of it away so that you can compare distant rows or columns with each other without losing track of what belongs where. Quite cool idea! Her homepage does not directly link to downloads of her software but she mentioned that by request there might be a way to get it.
The next talk that really grabbed my attention was by RobinWilkins which presented her and her co-authors' work on how the brain reacts to different types of music . For all persons in the experiment, the experimenter knew which song they loved most and which type of music they liked in general. The scientists put together a long record of all songs plus the favorite song of the respective test person. Looking at the working brain it became clear that the brain reacts totally different to songs it likes than to those it does not understand (music from a different culture) or those that it does not like. Especially, Wilkins et al. looked at how well the different parts of the brain, e.g., those doing the hearing or those concerned with emotions and memory, were synchronized during the different songs.
In summary: all of the talks were full of enthusiasm for bringing together arts, the humanities, and network analysis. It was just very refreshing to feel this enthusiasm, and I’ll make sure next time to register for Max’ great workshops at the earliest. So, please make sure you keep up the good work, Max!
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