Commercialism in Popular Music: Analysing brand mentions in song lyrics. Using Machine Learning to create lyrics in the style of different genres: Technical Report

Carroll, Conor (2021) Commercialism in Popular Music: Analysing brand mentions in song lyrics. Using Machine Learning to create lyrics in the style of different genres: Technical Report. Undergraduate thesis, Dublin, National College of Ireland.

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Abstract

In my report I will document my process of building a tool from scratch which is capable of identifying brand mentions within song lyrics. I will show how I get my raw data from the API provided by Genius.com, parse the data and create a data warehouse with all the brand mentions among other items of data.

I will also document how I created my list of brands to check for, using R programming language to web scrape lists from various sources on the net. The process I have built is usable for future artists going forward and could be modified to be used to check for other pieces of information within the music lyrics. I will be showing how I go about visualising the end dataset using Tableau.

Some analysis will be performed on the finished dataset and findings reporting. Some of the findings include, the rap genre has significantly more brand mentions than pop and country music and female and male rap artists tend to mention brands a similar number of times. I will also be looking at the correlation between Google Trends data and the number of times a brand is mentioned in that location.

As well as this, I will be documenting the creation of a Recurrent Neural Network in Python which is able to generate lyrics in the style of the three different genres looked at in this project. The Neural Network trains itself on the lyrics of genres and produces its own, based on the input data.

Item Type:	Thesis (Undergraduate)
Subjects:	M Music and Books on Music > M Music Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software
Divisions:	School of Computing > Bachelor of Science (Honours) in Computing
Depositing User:	Clara Chan
Date Deposited:	19 Aug 2021 13:58
Last Modified:	16 Sep 2021 16:05
URI:	https://norma.ncirl.ie/id/eprint/4984

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