Using Data to Analyze Hamilton

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I checked out the website Stephanie recommended in her blog post presentation (The Pudding), and stumbled upon an article that uses an interactive visualization to analyze the musical Hamilton. An Interactive Visualization of Every Line in Hamilton is the author Shirley Wu’s attempt to visualize the text of Lin Manuel Miranda’s Hamilton. Wu writes that she was interested in visualizing the relationships between various characters and the themes associated with them. To do this, she went through every single line of Hamilton and recorded who sang the line, who the line was sung about, and what themes the lines repeated in multiple songs expressed. She then created a visual tool that filters through the codes she attached to each line or group of lines.

Wu visualizes the data in a few different ways. First, if you scroll down a little on the web page, you’ll find an image of forty something clusters of colored dots. Each cluster represents a song, and each colored dot is a set of lines within the song colored coded by speaker. Just looking at this visualization can tell you a lot about the musical. For example, the colors that come up the most are purple and teal – the colors that represent lines spoken by Aaron Burr and Alexander Hamilton. These are the two main characters, so it makes sense that they have the most lines.

Next, Wu filters the results by relationships. Her next visualization filters lyrics by who is speaking and who is being spoken about. The page is automatically set to show lines where Alexander Hamilton and Angelica Schlyer speak to or about each other, but you can add characters to the visualization to further explore relationships.As you scroll down, Wu adds themes and recurring phrases to her visualization of the relationship between Angelica, Alexander, and Eliza. I thought this page was particularly interesting. I liked the idea of filtering the text of the musical by speaker and theme. It’s a cool way to visually see the importance or progression of relationships without having to read the entire text of the musical.

At the end of the article, Wu gives the reader a chance to try explore relationships and themes between any of the main characters of musical. This is where I started thinking about the limitations of the article. I realized that although I loved how Wu walked through the nuances of the relationships she highlighted earlier, she didn’t write enough about how to use her visualization for me to feel comfortable using it myself. I also noticed that oftentimes when I selected two charters, the visualization would show songs in which both characters spoke but didn’t interact with each other. This made it look like the characters had a more significant relationship than really did. Another big limitation in this article is potential bias and validity.  Can we trust that Wu interpreted the themes and relationships that she coded the way the author intended? I think the only way to eliminate bias would to confirm the codes with the creator.  

Despite some limitations, I thought the idea of using data to analyze a work of art was fascinating. The articles visualization tool made it easy to see how themes and relationships developed across the musical, and provided insights that would be difficult to come to just reading the text. I don’t think reading the data alone could replace reading (or watching or listening to, in this case) a text itself, but could help readers quickly and clearly analyse it.I would love to see data visualizations of other books or plays or musicals I enjoy and see what I could learn from them.

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