Theatrical Genre Prediction using Social Network Metrics

摘要

With the emergence of digitization, large text corpora are now available online which provide humanities scholars an opportunity to perform literary analysis leveraging the use of computational techniques. Almost no work has been done to study the ability of mathematical properties of network graphs to predict literary features. In this paper, we apply network theory concepts in the field of literature to explore correlations between the mathematical properties of the social networks of plays and the plays' dramatic genre. Our goal is to find metrics which can distinguish between theatrical genres without needing to consider the specific vocabulary of the play. We generated character interaction networks of 36 Shakespeare plays and tried to differentiate plays based on social network features captured by the character network of each play. We were able to successfully predict the genre of Shakespeare's plays with the help of social network metrics and hence establish that differences of dramatic genre are successfully captured by the local and global social network metrics of the plays. Since the technique is highly extensible, future work can be applied larger groups of plays, including plays written by different authors, from different periods, or even in different languages.