The Narratives in Graphs
Analyzing the texts of great songs, movie scripts, and literature through data science, text mining, and data visualization in R.
Behind the Project: Text Data Journalism
We all like to listen to music, read a text, or enjoy watching movies. We admire how artists arrange words into lines, lines into verses, and create sequences that deeply touch human emotions. True art holds the unique power to make us feel the artist’s exact emotional state during the creation of their masterpieces.
However, in the midst of a captivating melody or a fast-paced script, we sometimes miss the core feelings behind the words and the complex thoughts born out of them.
“True art is able to make us feel the artist’s emotional state while creating their masterpieces.”
The Narratives in Graphs was founded to bridge that gap. By combining a deep appreciation for the creative arts with rigorous technical analysis, this publication translates abstract emotional narratives into clear visual landscapes.
Technical Focus & Methodology
This project treats creative writing as rich, unstructured datasets. Using the R programming ecosystem, the analytical workflow systematically processes creative narratives across several mediums:
- Data Sources: Song lyrics, feature film scripts, contemporary short stories, and classic novels.
- Natural Language Processing (NLP): Sentiment analysis tracking emotional arcs, term-frequency evaluations ($tf\text{-}idf$), and word-cloud distributions.
- Data Visualization: Custom, high-fidelity plots engineered in R to map the invisible cadences of storytelling.
Explore the Analysis
If you want to read the latest deep-dives, explore interactive plots, and dive into the text analysis of your favorite songs and stories, visit the live publication below.