The remainder of the code scrapes the lyrics from the website or trips on an error 404 when it cannot find the song/artist combination. These two fields are then concatenated to create the URL, which the function prints. This code removes any character that is not a number or a letter, converts to lowercase and lastly removes the definite article in the artist name. The first three lines clean the artist and song variables. The first function scrapes song lyrics from the azlyrics website using the artist and song as input. The old reshape2 library helps to transform a matrix, and lastly, rvest helps to scrape song lyrics from the azlyrics website. The tidytext library uses the tidyverse principles to analyse text. I use the tidyverse series of libraries because it makes life very easy. The code below visualises song lyrics or poetry as suggested by Colin Morris. The next section shows how to implement this approach with ggplot, scraping pop song lyrics from the website. Towards the end of the song, we see the bridge, which is like a little snowflake within the diagram. After that we see diagonal lines appearing that represent the repetitive use of the song title. The first 30 words are the opening verse, which shows little repetition, other than stop words such as and the pronoun I. The diagram below visualises the lyrics of one of the most famous pop songs ever, Waterloo by Abba. As a result, the bridge is in most songs a unique pattern with self-similarity. Many songs have a bridge that contrasts with the rest of the song. A verse is not very repetitive besides some stop words. The verses are the gutters with only diagonal lines. ![]() The snowflake diagrams are a visual language to decode lyrics. Self-similarity matrix for Mary had a Little Lamb by Thomas Edison. It shows where the words "Mary", "lamb" and "was" are repeated once. The similarity matrix below visualises the two first sentences of the famous nursery rhyme. And everywhere that Mary went, the lamb was sure to go. Mary had a little lamb, whose fleece was white as snow.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |