Data visualization of language patterns and lyrical analysis of top Billboard charting songs over the 20th century.
What do popular song lyrics say about cultural moods, concerns and political issues of different times? To answer this question and because no database of this information existed at the time, a Python web scraping script was developed to pull lyrics from the top Billboard charts since its inception in the early 1900's. Using a Java based IDE and natural language processing, frequencies of noun entities (such as "I" and "you"), as well as common verbs that express relationships between those entities (such as "love", or "hate") were visualized.
With this data visualization, topical patterns over time became evident as song lyrics from different decades reveal societal patterns and trending topics.
Frequency of keywords were used to weight their size (more frequent use of a noun phrase resulted in a larger font size), and bézier curves to visualization semantic linkages between different keyword entities.
Creative director & developer of a data visualization examining language patterns in musical lyrics over time, revealing cultural trends and moods of different time periods as expressed in top-charting songs. Presented as large format digital images and print posters.