Probably for the best
I barely read my own post while writing, so youâre in good company!
We can tell.
Mission accomplished!
In conclusion, get off my lawn.
Here you go. Iâm leaving my biases out so that you can look at the study, methodologies, testing, results, and conclusions for yourself.
Thatâs the PDF I have attached
Understood, I wanted to provide the actual website to the study though, in case there were any links to other studies or references.
Important category definition in the study:
âIn this work, we investigate the dynamics of English lyrics of Western, popular musicâ
In other words, they are analyzing pop. This is not about comparing the lowball crap pop of today versus masterpieces from the past like New Dawn Fades; thatâs just amateur-level trolling, not science
I easily believe lyrics have gotten more concise and repetitive stylistically in the last few decades. That doesnât make the song objectively worse at its mission (i.e. sell a lot of copies for the pop producers and make their label rich, which is the mission of pop music). Letâs be realistic, no one is going to pop for its Shakespearean iambic genius.
I really ask myself, if they would use the same definition, ie seeing âNew Dawn Fadesâ as âpopular musicâ. I know, you wouldnât like it, but in Germany there is a distinction between âE-Musikâ and âU-Musikâ, E being âernstâ (earnest) and U being âUnterhaltungâ (entertainment). Popular Music is U, not E.
I have the feeling, that WIkipedia agrees with me: Popular music - Wikipedia.
âpopâ has itâs own article: Pop music - Wikipedia. Even here I might argue, that âNew Dawn Fadesâ is pop. It doesnât feel right, this might be the case!
Now I really want to see a list of songs they have analyzed!
Keep asking yourself, as your first answer was one that I think few would agree with
Joy Division were an English rock band formed in Salford in 1976.
Rock is a broad genre of popular music
You can try and semanitcally argue that Joy Division was pop all day; it doesnât make the assertion any less ridiculous in the sense of reasonable categorization
Iâm not going to play that game; nice try, though.
As a general comment, we donât really troll each other that much here. You can try but itâs really not the spirit of this site. Poke fun sometimes, sure - but itâs best to keep the discussions genuine.
I think their definition is somewhat broader than yours:
In particular, we extract lexical, linguistic, structural, rhyme, emotion, and complexity descriptors and focus on five genres: rap, country, pop, R&B, and rock, as these are the most popular genres according to the widely used music streaming platform last.fm (https://www.last.fm/)24,25,26,27, disregarding genres for which lyrics are less frequent (e. g., jazz and classical music).
I really did nor mean to make fun of it nor you. When it comes to scientific stuff I am quite serious.
In my opinion it is very important to have a common definition when discussing. I find, WIkipedia helps a lot!
That is interesting, and yes it is interesting to see their selection criteria (i.e. were these weighted by popularity on the platform? If so, thatâs still strongly biasing pop, which exists in all those genres; itâs interesting they separated pop out as thereâs pop rock, pop country, etc). I suspect the distinction is last.fmâs tagging and not their own analysis. For example, as stated in the study:
âThe second set of analyses investigates the relationship between lyrics view count, descriptors, and corresponding songsâ release year in a multiple linear regression analysis. Assessing lyricsâ view count, besides the typically analyzed measure listening play count, enables us to take into account another perspective of music popularity.â
and later
âFirst, we perform z-score normalization of the descriptors. Subsequently, we remove multicollinear descriptors using the variance inflation factor (VIF). Here, we iteratively remove descriptors that exhibited a VIF higher than 5 until all of the remaining descriptors have a VIF lower than 5 (as also performed in Analysis 2).â
i.e. they are first sanitizing the data by discarding outliers, and given that listen count is a primary criteria they used, this would bias towards pop.
I think this is a perfectly sound approach if the goal is to analyze Popular music.
Note that they also describe their own study as analyzing pop music:
"Subsequently, we evaluate the evolution of pop music lyrics over time within each musical genre. "
Thereâs also an interesting discussion in there about how they normalized the dataset across genres to retain popularity as a selection criteria; i.e. pure pop has a vastly higher listen count than pop country, so the genres needed normalization as well. All in all the paper is an interesting study.
I know where you want to go, but even with the definitioon of âpopâ using Wikipedia, you get this: âIdentifying factors of pop music usually include repeated choruses and hooks, short to medium-length songs written in a basic format (often the verseâchorus structure), and rhythms or tempos that can be easily danced to. Much pop music also borrows elements from other styles such as rock, urban, dance, Latin, and country.â
You cannot have more HOOKs than in Joy Division
If our conclusion would be that they sanitize the data in a way that only songs are selected that were âpopularâ, than the songs they selected should have appeared in the charts or in (heavy) rotation.
And even then you will find some Joy Division songs in their data (maybe not âNew Dawn Fadesâ) as they a) had songs in the charts and b) were in heavy rotation (at least in Germany and Belgium).
We have to accept that Joy Division made âpopular musicâ and might even be âpopââŚ
So that means that it is likely that their music and other music we love appeared in the data to be analyzed, which explains that the lyrics were - accordinbg to them - much âricherâ in the good old days!?
Again, not interested in semantically lawyering the definition here as itâs clear to anyone reasonable that early post-punk bands like Joy Division were not '70s pop.
The paper itself is much more intellectually honest about biases there:
"Given the nature and history of these platforms, in particular last.fm, the studied LFM-2b dataset is affected by community bias and popularity bias. "
i.e. the dataset is skewed towards things that are popular to the last.fm community.
Good paper, I am glad I read it.
Ok, usually I agree with everything you say (except about the ugly Ibanez :-)).
But I find it hard to argue against âanyone reasonableâ, as this has no scientific value for me ^^
Letâs leave it at that, so things donât heat up!?