After doing some exploratory diving into complex network analysis for finding out more about the character interactions in the Innsbruck Easter Play and not really being satisfied with the outcome (Part I), I have decided to continue working with this play and will be writing about it in a number of blog posts.

I’ve done some more work, mainly:

Created a .csv file for all ‘interactions’ of characters in the play.

By interactions I mean verbal and non-verbal communication directed to one or more characters (including the audience) as well as movement towards a stage location. I have even included the interaction of characters with objects of Christian symbolism (the shroud Jesus was buried in). Thus, the nodes in my graph can be characters (persons), stage locations (places), and objects (objects). The (…) serve as node attributes. The edges are the directed interactions between nodes. I have classified them into a number of ‘speech interactions’, ‘movement interactions’, and ‘physical interactions’. These serve as edge attributes. I have manually extracted these interactions from the stage directions of the play and in a few cases from the dialogue text. In quite a few cases, though, I had to leave a node blank because it wasn’t clear whom or what the interaction is directed at. I didn’t want to leave this information out so I decided to include it at this stage and create a special node “Ignotus” (unknown) instead. I will try to look deeper into the text to determine who or what is the target of the interaction in the unknown cases.

To get an impression of the interactions, lets take a look at an example from the text of the Innsbruck Easter Play (lines 147-166):

Nuntius recedit et vadit ad Pylatum et dicit
(The messenger steps back and goes to Pilate, and says:)

Edeler konnig Pylate,
dir enpiten vyer ritter drate,
daz sy wollen czu dir komen,
alz von dir haben vornamen.

Pylatus dicit
(Pilate says)

Ge hen vnd heiz sy czu mir komen,
ez wert er ere vnd ouch er frame:
ich muz sy czu noten haben,
wen da ist nymant by dem grabe.

Nuntius dicit ad Pylatum
(The messenger says to Pilate):

Pylate, lyber here myn,
laß dir dy wile nicht lang sin.

Nuntius exit et conducit milites ad Pylatum cantans Judaicum
(The messenger exits and leads the soldiers to Pilate, singing in Hebrew)

[Chodus chados adonay … amel!]

Angeli
(The angels)

‚Siletis’

And here’s how that looks in my spreadsheet, from row 57:

source label target
Nuntius EILEN Pilatus
Nuntius SPRECHEN Pilatus
Pilatus SPRECHEN Nuntius
Nuntius SPRECHEN Pilatus
Nuntius GEHEN Ignotus
Nuntius BRINGEN Primus Miles
Nuntius BRINGEN Secundus Miles
Nuntius BRINGEN Tertius Miles
Nuntius BRINGEN Quartus Miles
Primus Miles GEHEN Pilatus
Secundus Miles GEHEN Pilatus
Tertius Miles GEHEN Pilatus
Quartus Miles GEHEN Pilatus
Primus Miles SINGEN Ignotus
Secundus Miles SINGEN Ignotus
Tertius Miles SINGEN Ignotus
Quartus Miles SINGEN Ignotus
Primus Angelus RUFEN Spectantes
Secundus Angelus RUFEN Spectantes
Tertius Angelus RUFEN Spectantes

As you can see, I have decided to handle groups of characters as individuals. This is mainly because all groups (angels, soldiers, the Marys, and the Jews) also have their members acting individually with their own dialogue and interaction. One could argue that the group makes for an individual node apart from the individuals of the group making a node also, but for this part, I have chosen to list individuals only. You can also see the infamous “ignotus”-node – in the case above it is not entirely clear whom the soldiers sing their song to: it is definitely not directed towards either Pilate or the messenger, nor is it directed towards the audience. You could argue that I might as well skip it, because the action “singing” happens simultaneously with the action “walking”, making it rather a type of walking than two different actions. I haven’t decided on how to handle cases like this one (there’s several), but for this test, I recorded a maximum of interaction and characters.

After collecting the character-interaction-information from the text of the play in this edge list, I have created a graph visualization with the tool Gephi. The result looks like this:

Character network visualization of the Innsbruck Easter Play

The visualization looks quite different from Part I, mainly, because I have run some analytics on the graph (you can do all this with Gephi, it’s quite powerful!) and used directed, parallel edges. What the visualization shows is ‘amount of interaction’ between nodes with the thicker the edge line, the more interaction. And it shows the ‘connectedness’ of characters by node size: the more (different) connections a character has to another, the bigger the node.

However, if you pay close attention to the graph, you will see that I have not separated types of nodes or types of edges: the graph doesn’t differentiate between persons or places, nor does it take the types of interactions into account (I’ve played around with the settings for this but apparently didn’t take a picture – so, “it didn’t happen!”). The other issue is the big “Ignotus” node, that could be anything from an individual person, a group of characters or a place. I don’t like this, but at the moment, there’s not much I can do about it, since it involves a couple of hours of manual text analysis to decide where interactions are directed towards. I will leave it at this. For the next part, I will hopefully have dealt with the issue and gotten the data cleaned so I can finally embark on the analysis part of the character network of the Innsbruck Easter Play.

You can do your own analytics with my data – it’s all (in a bit of a mess) in my GitHub repository InnsbruckEasterplay.

Stay tuned!


Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.