For the past year, a good portion of people living in the U.S. have been obsessed with Lin-Manuel Miranda’s Hamilton, the award-winning musical about its titular figure, Alexander Hamilton. Lauded for both its musical and lyrical brilliance as well as its intentionally diverse cast, Hamilton uses hip hop, rap, and other non-traditional musical styles to tell the story of Alexander Hamilton’s short but dramatic life, creating an intriguing narrative that has resonated with millions.
I decided to run an analysis on the lyrics from the first act of the musical. Act One consists of 23 songs and covers Hamilton’s life from birth & hardship in the Caribbean in the first song to his arrival in New York & leadership roles during the War for Independence. As a fan of the musical, I know the plot and themes well, but I wondered if Voyant Tools would reveal otherwise unnoticed patterns in the language Miranda uses to convey the story. I knew that the musical utilizes repetition multiple times, and wanted to know if the words that were used most frequently correlated with one of the themes that the narrative continues to circle back toward throughout the play.
My first step was to copy and paste the lyrics into the Voyant Tools text box. The lyrics, which I found on Genius, included the character names for each part, so I had to remove those in TextEdit before pasting into Voyant Tools.
As it turns out, the most frequent words were “i’m” (135), “da” (90), “hey” (60), “wait” (59), and “shot” (56). I adjusted the stopwords for “i’m,” “hey,” “like,” and “you’re” because they were words used frequently but with less of an impact on the actual storyline. I also took out “da” and “dat” as they were onomatopoeic scatting during the King George songs, which would’ve skewed the data towards the two songs rather than getting an overall picture.
I looked at the Cirrus tool, which generated a word cloud by analyzing the frequency of words used. Because “wait” was the largest and most central word in the cloud, it was immediately clear that it was the most frequent, closely followed by the word “shot.” This was a helpful visualization of what I already knew, as someone who was familiar with the Hamilton album. The word “wait” was incorporated into songs like “Wait For It,” when the character of Aaron Burr sings about biding his time to make the most informed decision towards success in the political arena, but is also a constant refrain throughout the musical, at times framed as a cautionary device in opposition to the Hamilton character’s tendency to rush headfirst into conflicts. Other large, central words were “shot,” “time,” and “look,” words that fit into the show’s theme of not “throw[ing] away [their] shot,” “running out of time,” and “look[ing] around” and being grateful for what they have. What surprised me was that the word “Hamilton” was less frequent than I thought it would be, considering the musical’s central character, and that there were other words like “work” that were large as well but only featured prominently in one song.The Trends tool was helpful in visualizing when and where certain words were used most in the overall timing of the first act, and I was able to see where the song “My Shot” fell in relation to “Wait For It” with the two tallest arcs on the graph (blue for “shot” on the left, green for “wait” on the right). The line for “look” (red) was interesting because it seems to have the most consistency in frequency through the first act, cropping up at the 3rd, 5th, and 8th sections. Though helpful as a visualization tool, I wish there was a way to analyze the song lyrics by inputting the song times into the x-axis to see where in the emotional arc of the plot these words were being used. The Bubbles tool was also great as an animated visualization of the frequency of words, and it was amazing to see and hear the tool work as it went through the corpus of lyrics. It showed that many of the words were used again and again throughout the first act and that the writer cycled back to certain words frequently.
Some of the other tools I tried were the Bubblelines tool and the Phrases tool. It seemed that with the body of words I input into site, Trends, Bubbles, and Bubblelines all served the same purpose in different ways. Each tool showed the frequency of words used over time, but with varying methods of visualization. These can all be useful for that purpose, but looking at all three did not yield very diverse results. Additionally, my question at the beginning, wondering if Voyant Tools would show me something unseen in the text, was answered with a resounding “no,” most likely because the lyrics from Hamilton are less complex than I previously thought. In that vein, I probably should have used a different text to test this site, one that would have yielded more empiric data with which to work. As it stood, playing around with Voyant Tools allowed me to get a clearer picture of trends I had already suspected from my intimate familiarity with the musical’s lyrics, plot devices, and themes.