Drake — Using Natural Language Processing to understand his lyrics
Every couple of years there is an artist who seems to take the world by storm. In the past, this has been The Beatles and Michael Jackson, among others. These artists have the intrinsic ability to influence millions with their creative genius. It seems that when we started the second decade of the 21st century, a multitude of artists were jockeying to be number one. However, perhaps unexpectedly, a Toronto native by the name of Aubrey Graham ascended to the top under the stage name “Drake.”
Drake’s original claim to fame was from his role on the popular teen sitcom “Degrassi: The Next Generation” in the early 2000s. However, Drake left the show when he figured he wanted to become a rapper. Lil Wayne, one of the most influential rappers at that time, made the Toronto Native his protege. After signing with Wayne’s record, Young Money Entertainment, Drake released his first Studio Album, So Far Gone. It was certified Platinum and expedited Drake’s rapid ascent to the top of the hip hop world. Over the course of the next eight years he dropped four additional studio albums, a mixtape, and a playlist, with Scorpion being his most recent release (source).
We know for a fact that Drake’s work is popular but why are the majority of his songs such a hit? Is it the production? Is it the marketing? It is probably a combination of factors. However, the aspect I will be focusing on is his lyrics. Drake’s work is expansive and well-documented, so getting text data was not a difficult task. However, figuring out how to analyze it was. But thanks to recent improvements in NLP (Natural Language Processing), analyzing text data is now easier than ever.
According to Wikipedia, Natural Language Processing (NLP) “ is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.” NLP is the most interesting field of machine learning in my opinion. Text is produced in so many different forms, its gives us so much data to work with.