Social Networks: The Aeneid Again

Applying social network analysis techniques to the Aeneid provides an opportunity to visualise literary concepts that Virgil envisaged for the text. It occurred to me that this was a great idea when I saw this social network analysis of Game of Thrones. If there is a group of literary figures more blood thirsty, charming and messed around by cruel fate than the denizens of Westeros, it would be those in the golden age of Roman literature.

Aeneid social network

This is a representation of the network of characters in the Aeneid. Aeneas and Turnus, both prominent figures in the wordcloud I created for the Aeneid are also prominent in the network. Connected to Aeneas is his wife Lavinia, his father Anchises, the king of the Latins (Latinus) and Pallas, the young man placed into Aeneas’ care.

Turnus is connected to Aeneas directly along with his sister Juturna, Evander (father of Pallas. Cliff notes version: the babysitting did not go well) and Allecto, a divine figure of rage.

Between Aeneas and Turnus is the “Trojan contingent”. Virgil deliberately created parallels between the stories surrounding the fall of Troy and Aeneas’ story. Achilles, the tragic hero, is connected to Turnus directly, while Aeneas is connected to Priam (king of Troy) and Hector (the great defender of Troy). Andromache is Hector’s widow whom Aeneas meets early in the epic.

Also of note is the divine grouping: major players in directing the action of the epic. Jupiter, king of the gods and Apollo the sun god are directly connected to our hero. Venus, Neptune, Minerva and Cupid are all present. In a slightly different grouping, Juno, Queen of the Gods and Aeneas’ enemy is connected to Dido, Aeneas’ lover. Suffice it to say, the relationship was not a “happily ever after”.

I used this list of the characters in the Aeneid as a starting point and later removed all characters who were peripheral to the social network. If you’re interested in trying this yourself, I posted the program I used here. Once again, the text used is the translation by J.W. Mackail and you can download it from Project Gutenberg here.

There were a number of resources I found useful for this project:

  • This tutorial from R DataMining provided a substantive amount of the code required for the social network analysis
  • While this tutorial from the same place was very helpful for creating a text document matrix. I’ve used it previously a number of times.
  • This article from R Bloggers on using igraph was also very useful
  • There were a number of other useful links and I’ve documented those in the R script.

Whilst text mining is typically applied to modern issues, the opportunity to visualise an ancient text is an interesting one. I was interested in how the technique grouped the characters together. These groupings were by and large consistent not only with the surface interpretation of the text, but also deeper levels of political and moral meaning within the epic.

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