The Rhymes Behind Hamilton

The Rhymes Behind Hamilton

Organisation: The Wall Street Journal (United States)

Publication Date: 03/31/2017

Size of team/newsroom:large

Description

An unlikely candidate for data visualization, “The Rhymes Behind Hamilton” uses an algorithm to analyze the complex rhyming structure and inspiration behind the Broadway hit, “Hamilton: The Musical.” Using an algorithm developed by Wall Street Journal graphics editors Erik Hinton and Joel Eastwood, the piece identifies and visualizes the rhyming structures that make the lyrics so powerful and memorable, drawing comparisons with other songs that inspired creator Lin Manuel-Miranda. The visualization uses diamond shapes and color-coded patterns along with music clips to create vivid representations of something that’s rarely visualized: the hidden structure of rhymes. The process of making it was written about here: https://source.opennews.org/articles/hamilton-algorithm/. Read more about the data methodology here: http://graphics.wsj.com/hamilton-methodology/

What makes this project innovative? What was its impact?

The project relies on a rhyming algorithm built in-house by Erik Hinton and Joel Eastwood. The team described their process in an academic paper presented at Stanford University’s Computation and Journalism conference: “The algorithm relied on speech phonetic research to quantify rhyming and sounding similar, as well as graph and genetic algorithms to cluster and optimize the subsequent rhyme families.” (https://journalism.stanford.edu/cj2016/files/Writing%20an%20Algorithm%20To%20Analyze%20and%20Visualize%20Lyrics%20From%20the%20Musical%20Hamilton.pdf). Beyond the complexity of the algorithm, the piece relied on a playable audio-driven data visualization, which was developed after several drafts and failed attempts to clearly communicate the relationship between audio, rhymes and non-rhyming syllables. In the process, we discovered a new element for digital data visualization: time. By playing the audio, we could introduce each syllable one at a time. This solved a problem with trying to squeeze in too many words at once. Finally, the project included a create-your-own visualization tool, which required translating the algorithm into web-friendly languages and streamlining the calculations so they would work seamlessly on the phone. The impact was massive. Lin Manuel-Miranda, creator of Hamilton, tweeted this about the project: “So @wsj is unpacking Nas & Rakim & Pun for the masses, & It took a musical to get 'em there. The [world] turned [upside-down]” (https://twitter.com/Lin_Manuel/status/739821762683211777). Dozens of articles were written about the project. Hundreds of rhymes were analyzed by our readers using the tool. Teachers tweeted that they were using the interactive component to teach students about poetry, an unintended but desirable outcome.

Technologies used for this project:

- Syllable analysis done with annotated CMU Pronouncing Dictionary - Modeled in Python, nltk and networkx - Ported to Javascript - Used jsnetworkx to build graph of rhyming relationships between syllables - Used the Markov Clustering Algorithm (implemented here https://github.com/nikezono/mcl) to clustering the network graph into families of rhyming syllables - Used a hand-rolled simulated annealing algorithm to order rhyme families (in the final viz) to make more perspicuous patterns - UI and viz mocked up in terminal, printing colored shapes to terminal to experiment without having to roll a front-end - The visualization was created using D3 and was paired to MP3s using the jPlayer library.
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