Latent dimensions of Star Wars: Social network analysis of a galaxy far, far away [TAKEN]

Are the connections between the Star Wars characters more than meets the eye? In this project, data on interactions between Star Wars characters (from an episode of the students choosing)

are studied through the lens of latent space models. This model can construct a latent social space that reveals the underlying structure of this iconic network. The underlying assumption of the Latent Space Model is that two characters are more likely to interact with one another if they are close to one another in that latent social space.  Utilizing a readily available implementation of Latent Space Models in R, we decode the latent positions of characters to understand the forces that drive narrative cohesion and character development. This analysis may provide a novel quantitative perspective on the Star Wars saga and showcase the potential of latent space models. This project offers a unique toolkit for examining the social interactions that shape the stories in a galaxy far, far away.  A working knowledge of the programming languages R or Python and statistical regression models is strongly advised to work on this project. All interested students must first email fritzc@tcd.ie to set up a short informal meeting to discuss the project.  

Relevant literature:

Hoff, Raftery, &. Handcock (2002). Latent Space Approaches to Social Network Analysis. Journal of the Americal Statistical Association 

https://www.stat.cmu.edu/~brian/905-2009/all-papers/hoff-raftery-handcock-2002-jasa.pdf

https://github.com/evelinag/star-wars-network-data