Social Network Analysis of co-occurring comic characters

Another thing I learned at my librarian job is that Social Network Analysis (SNA) methods seem to become increasingly popular in the Humanities. The basic idea of SNA is that you define a type of entity as nodes (actors), and some criterion for establishing edges (connections) between them. Once you have constructed such a network, you can analyse it by applying various mathematical operations. The difficult part is defining your nodes and particularly your edges in a way that is both feasible and meaningful.

Some Literature scholars have tackled this problem by using SNA for drama. Written plays are highly structured: speakers are indicated in fairly standardised ways, so that they can be used as nodes in a network. Edges between them can be formed by looking at which characters are on stage at the same time (i.e during the same scene), possibly indicating a dialogue or other interaction. Another benefit of using drama for SNA is that many older texts are available digitally. Crowdsourcing may be used to clean up this data, thus making it machine-readable for SNA purposes. The resulting graphs may provide insight into certain historic developments, e.g. the number of characters per play increasing over time (PDF, German).

In comics, such automatic processing is still a distant dream, but on a smaller scale, networks may be constructed manually. Identifying nodes is more problematic in comics, though, because unlike in drama, characters aren’t explicitly named each time they appear. They usually have to be identified by their looks, which isn’t always easy. Another problem is how to define the edges. A research group from Paderborn recently proposed (PDF, German) to establish an edge between two characters whenever they appear on a page together. In my opinion, a more suitable category than the page would be the panel, as there are sometimes narrative shifts between panels on the same page, so that the co-occurrence of characters on a page doesn’t necessarily imply interaction. Furthermore, some comics don’t have pages, but they all have panels.

To test the feasibility of this approach, I built a little character network based on co-occurrence within panels, once again using Akira. Here is a Gephi rendering of such a network from the first 16 pages of volume 3 (blue numbers indicate the number of panels on which both of the connected characters appear):

Character co-occurence network of Akira vol. 3, pp. 5-20I assigned the group of soldiers to one single node rather than one node per visible soldier, similar to a speaker designation for groups of people in a play. As we will see in the second example, these ‘crowd’ nodes may cause some headache. Anyway, the most striking thing about this network is that it consists of three unconnected clusters. In other words, the action takes place at three different places on these 16 pages: the military base, Miyako’s temple, and the streets of Neo Tokyo. (Actually there are two more locales – the site of the SOL laser beam impact and SOL in space – but no character interaction takes place there.) Keep that in mind as we look at the first 17* pages of the 4th volume:

character co-occurrence network of Akira, vol. 4, pp. 4-20

2 panels from p. 13 of Akira vol. 4 by Katsuhiro Ōtomo

Spot the Lieutenant.

At first glance, this graph is very different from the first: instead of three clusters, there is one small and one large cluster. However, this impression is misleading. Because I lumped all of Tetsuo’s henchmen together as “Great Tokyo Empire mob”, they act as a bridge between the actually unconnected scenes at the rescue helicopter on the one hand, and Lieutenant Yamada and his diving unit entering the city on the other. (Another problem here is that Yamada can’t be recognised until he takes off his diving suit – for simplicity’s sake I just assumed he is always among the group of divers depicted.)

Thus we can tentatively recognise a pattern in Ōtomo’s storytelling: rather than building his story around one central protagonist, he frequently jumps between parallel lines of action, with shifts taking place approximately every 2-8 pages.


*Why the different number of pages (16 and 17, respectively)? The reason is that I analysed both volumes until p. 20, but vol. 3 starts on p. 5, whereas vol. 4 starts on p. 4.
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