For hundreds of years, scholars have carefully studied the plays of Shakespeare, breaking down the language and carefully dissecting every act and scene. We thought it would be interesting to see what sorts of computational insights Wolfram|Alpha could provide, so we uploaded the complete catalog of Shakespeare’s plays into our database. This allows our users to examine Romeo and Juliet, Macbeth, Othello, and the rest of the Bard’s plays in an entirely new way.
Entering a play into Wolfram|Alpha, like A Midsummer Night’s Dream, brings up basic information, such as number of acts, scenes, and characters. It also provides more in-depth info like longest word, most frequent words, number of words and sentences, and more. It’s also easy to find more specific information about a particular act or scene with queries like “What is the longest word in King Lear?”, “What is the average sentence length of Macbeth?”, and “How many unique words are there in Twelfth Night?”.
These queries can be used to analyze multiple plays at same time as well:
Asking Wolfram|Alpha for information about specific characters is where things really begin to get interesting. We took the dialog from each play and organized them into dialog timelines that show when each character talks within a specific play. For example, if you look at the dialog timeline of Julius Caesar, you’ll notice that Brutus and Cassius have steady dialog throughout the whole play, but Caesar’s dialog stops about halfway through. I wonder why that is?
Wolfram|Alpha can also provide an analysis of just a specific act or scene of a play. The query “The Merchant of Venice, Act 2, Scene 5” brings up the data analysis for just that part of the play. Getting more specific is also possible, like finding the exact number of words in a specific act and scene of a play:
In addition to Shakespeare’s plays, Wolfram|Alpha can also analyze other famous works of literature, including Moby Dick, Great Expectations, and Adventures of Huckleberry Finn. We hope you enjoy being able to perform computational analysis on these texts and would love your suggestions on new features and texts to add.