Extracting Sentiment Networks from Shakespeare's Plays

Automatic methods for analyzing sentiment and its movement through a play's social network are investigated. From structured dialogue we can algorithmically determine who is speaking and guess at who is listening or being directly addressed. Knowing who is speaking to whom allows the flow of sentiment to be tracked between characters and, within plays with clear time-lines, permits tracking the development of emotional relationships. We hypothesize that changing polarities between characters can be modeled as edge weights in a dynamic social network- a "sentiment network"-which can be used to distinguish a document's genre (tragedies versus comedies), detect a given character's enemies and allies, and model the overall emotional development of a play. Experiments on Shakespeare's plays are presented along with discussion of improvements and further applications.