SINCE the social network has taken up the center stage in
every aspect of our life, the indicator of the popularity in the
entertainment business has been shifted. Especially in the music
scene, the record sales or the frequent exposure to the major media
yields their limelight to the new medium, the social network and
youtube. The number of followers of the social network and the
subscribers of youtube can be the reliable proof for the popularity
of the pop artists? How can these numbers be related with the
commercial success of the song? This project started from these
questions.
Featuring is the particular type of creative collaboration
involving one artist integrating another artist’s contribution,
either instrumentally or vocally, into their work and publicizing it
with a "featuring" credit. It has become the key element to the
music fan ‘who feat. whom’ and played a significant role in the
marketing and publicity for the song even before the release.
“Guess Billboard Hot 100?” is an interactive platform to
choose two artists, “who ‘FEAT.’ whom” and provide the expected rank
on Billboard Hot 100 Chart based on machine learning technology.
What we want to examine with this platform is the plausibility
of an artist's popularity on Social networks for the song’s success
on the chart rather than the music’s quality itself.
1. Data for Featuring
Among the songs of the Billboard Hot 100 Chart from 2010 to 2020, We
select the ‘FEATURED’ songs of two artists’. The highest rank of the
song and the two artists are the main factors.
2. Data for Artists
The number of the subscribers of Youtube and the total sum of
followers of social networks are the basic data for each artist.
3. Model and Training
We combine ‘Data for Featuring’ and ‘Data for Artists’ to generate a
dataset. The prediction model is generated by Keras’ Sequential
model.
Comparison of the actual rank with the predicted result by the
platform on the Billboard Hot 100 Chart in June 2021
MAIN ARTISTS | FEAT. ARTISTS | SONG | ACTUAL | PREDICTION |
---|---|---|---|---|
Future | Lil Uzi Vert | Drankin N Smokin | 31 | 24 |
A Boogie Wit Da Hoodie | Lil Durk | 24 Hours | 88 | 94 |
J. Cole | Bas | 1 0 0 . m i l’ | 14 | 28 |
Machine Gun Kelly | blackbear | my ex’s best friend | 20 | 2 |
J. Cole | Lil Baby | p r i d e . i s . t h e . d e v i l | 7 | 29 |
Maroon 5 | Megan Thee Stallion | Beautiful Mistakes | 13 | 24 |
H.E.R. | Chris Brown | Come Through | 64 | 45 |
Polo G | G Herbo | Go Part 1 | 86 | 65 |
Polo G | DaBaby | Party Lyfe | 85 | 85 |
Migos | Polo G | Malibu | 65 | 54 |
By testing several pairs of artists on this platform, we can provide
the hypothetical ‘Feat’ pair and predict its rank on the chart. We
also can see that it is possible to predict the song’s hit on the
chart only by the indicators of the popularity on social networks.
Even in the same pair of the artists, the vice-versa of ‘WHO’ feat
‘Whom’ leads to the different outcome on the chart. While
establishing the data set, the numbers of the followers and
subscribers are steadily changed(mostly added). A consistent
check-up is needed to keep it up.
For further development, other factors besides the artists’
popularity, like the artists’ creative capacity(the composing or
producing skill), the budget for the production and promotion will
be added for more prediction.
Images of artists used on this platform are taken from Wikimedia Commons.