When completing my research, I used Python to look at the data qualitatively and quantitatively. After tokenizing the lyrics, I looked at the most common words used in song lyrics from the Billboard Hot 100 lists spanning from 2000 to 2015. Based on the types of words that were returned, I narrowed them down by subject matter. This helped give insight into what topics were sung about most often in top songs.
To conduct the research, I found the dataset on Kaggle that listed the Billboard Hot 100 songs along with year, artist, and lyrics. While conducting the analysis, I put some work into Excel where I took out most of the stopwords that are called out through Python. I chose to leave the stopwords "she", "he", "his", "hers", "girl", and "boy" to gain information around which genders were sung about most often based on my research prior to executing my analysis.
