Predicting song popularity based on Spotify's audio features: insights from the Indonesian streaming users

Figures & data

Table 1. List of variables for analysis.³

Variable name	Definition	Data type
Popularity	The popularity of the track. The value will be between 0 and 100, with 100 being the most popular.	Integer
Popularity Class*	Four classifications of popularity based on [Popularity] score: 0–1: Unpopular 1–23: Low popularity 23–40: Moderate popularity > 40: High popularity	Integer
Acousticness	A confidence measure from 0.0–1.0 of whether the track is acoustic. 1.0 represents high confidence that the track is acoustic.	Float
Danceability	Danceability describes a track's suitability for dancing based on musical elements, including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is the least danceable, and 1.0 is the most danceable.	Float
Energy	Energy measures from 0.0–1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy.	Float
Duration	The duration of the track in milliseconds.	Integer
Instrumentalness	Predicts whether a track contains no vocals. “Ooh” and “aah” sounds are treated as instrumental in this context. Rap or spoken word tracks are clearly “vocal.” The closer the instrumentalness value is to 1.0, the greater the likelihood the track contains no vocal content. Values above 0.5 represent instrumental tracks but with higher confidence as the value approaches 1.0.	Float
Valence	A measure from 0.0 to 1.0 describes the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, and euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, and angry).	Float
Tempo	The overall estimated tempo in beats per minute (BPM). In musical terminology, the tempo is the speed or pace of a given piece and derives directly from the average beat duration.	Float
Liveness	Detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides a strong likelihood that the track is live.	Float
Loudness	The overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track and help compare the relative loudness of tracks. Loudness is the sound quality that is the primary psychological correlate of physical strength (amplitude) – values typically range between −60 and 0 dB.	Float
Speechiness	Speechiness detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audiobook, poetry), the closer to 1.0 the attribute value. Values above 0.66 describe tracks that are probably made entirely of spoken words. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including such cases as rap music. Values below 0.33 most likely represent music and other non-speech-like tracks.	Float
Mode	Mode indicates the modality (major or minor) of a track, the type of scale from which its melodic content is derived. Major is represented by 1, and minor by 0.	Integer
Explicit	Whether or not the episode has explicit content (true = yes it does; false = no it does not OR unknown).	Integer
Key	The key the track is in. Integers map to pitches using standard Pitch Class notation. e.g. 0 = C, 1 = C♯/D♭, 2 = D.	Integer
Time Signature	An estimated overall time signature of a track. The time signature (meter) is a notational convention to specify how many beats are in each bar (or measure).	Integer
Release Date	The year the episode was first released, for example, “1981-12-15”. Depending on the precision, it might originally be shown as “1981” or “1981-12”.	Integer

* The Author proposes this target classification variable. Other variables are from the original Spotify API documentation.

Table 2. Classification algorithm comparison.

Classifier	Overall accuracy	F1-score
Random Forest*	0.6974	0.6944
Extra Trees	0.6807	0.6781
Gradient Boosting	0.6750	0.6713
Multi-Level Perceptron	0.6646	0.6600
AdaBoost	0.6117	0.6017
Decision Tree	0.5996	0.5997
Logistic Regression	0.5727	0.5615
K-Nearest Neighbors	0.5574	0.5559
Extra Tree	0.5222	0.5229
Nearest Centroid	0.5001	0.4776
Bernoulli Naïve Bayes	0.4873	0.4632
Quadratic Discriminant Analysis	0.4720	0.4584
Radius Neighbors	0.4218	0.4169

* Random Forest has the highest overall accuracy and F1-score with maximum depth = None and number of estimators = 250, using 20-fold Cross Validation (mean = 68.87%, std = 0.79%).

Table 3. Regression algorithm comparison.

Regressor	R-2 Score	RMSE
Extra Trees*	0.6857	12.33
Random Forest	0.6824	12.39
XGBoost	0.6669	12.69
Decision Tree	0.6407	17.85
Gradient Boosting	0.6279	13.41
MLP Regressor	0.6259	13.45
AdaBoost Regressor	0.5131	15.34
SVR	0.5082	15.42
K-Neighbors	0.4866	15.75
Linear Regression	0.4253	16.67
SGD Regressor	0.4235	16.69
Extra Tree	0.3433	17.82

* Extra Trees Regressor has the highest R-squared and RMSE with maximum depth  = 32 and number of estimators = 250, using 20-fold Cross Validation (mean = 67.55%, std = 0.96%).

Figure 1. Confusion matrix for random forest classifier.

Table 4. Random forest classification report.

Class*	Precision	Recall	F1-Score	Support
0	0.81	0.89	0.85	5953
1	0.65	0.62	0.63	5787
2	0.67	0.59	0.63	5668
3	0.65	0.69	0.67	5781
Accuracy	0.70	23189
Macro Avg	0.69	0.70	0.69
Weighted Avg	0.69	0.70	0.69

* Class: 0 = Unpopular, 1 = Low Popularity, 2 = Moderate Popularity, 3 = Highly Popular.

Figure 2. Feature importance based on random forest classifier.

Table 5. Tukey's test from ANOVA Post Hoc.

Dependent variable	(I) Popularity coded	(J) Popularity coded	Mean difference (I-J)	Sig.
Duration	3	0	17317.555*	0.000
		1	22345.544*	0.000
		2	33956.568*	0.000
Release Date	3	0	45.958*	0.000
		1	24.460*	0.000
		2	10.533*	0.000
Danceability	3	0	.035*	0.000
		1	.039*	0.000
		2	-.010*	0.000
Energy	3	0	.268*	0.000
		1	.151*	0.000
		2	.070*	0.000
Loudness	3	0	5.753*	0.000
		1	3.419*	0.000
		2	2.082*	0.000
Speechiness	3	0	-.135*	0.000
		1	-.037*	0.000
		2	-.126*	0.000
Acousticness	3	0	-.454*	0.000
		1	-.280*	0.000
		2	-.132*	0.000
Instrumentalness	3	0	-.270*	0.000
		1	-.155*	0.000
		2	0.005	0.304
Liveness	3	0	-.030*	0.000
		1	-.040*	0.000
		2	-.057*	0.000
Valence	3	0	.014*	0.000
		1	.007*	0.019
		2	-.043*	0.000

* Class: 0 = Unpopular, 1 = Low Popularity, 2 = Moderate Popularity, 3 = Highly Popular.

Figure 3. Histogram plot of the audio features on the four popularity classes.

Table 6. Descriptive statistics for each class.

Descriptives	Class	N	Mean	Std. Deviation
Duration	0	23,455	221,145.860	216,468.416
	1	23,333	216,117.880	167,086.952
	2	22,809	204,506.850	104,192.619
	3	23,158	238,463.420	105,164.426
Release Date	0	23,455	1,947.520	26.219
	1	23,333	1,969.020	26.781
	2	22,809	1,982.950	14.947
	3	23,158	1,993.480	17.635
Danceability	0	23,455	0.524	0.178
	1	23,333	0.519	0.166
	2	22,809	0.569	0.150
	3	23,158	0.559	0.158
Energy	0	23,455	0.308	0.214
	1	23,333	0.426	0.264
	2	22,809	0.507	0.229
	3	23,158	0.576	0.238
Loudness	0	23,455	−14.65	5.851
	1	23,333	−12.32	5.553
	2	22,809	−10.98	4.608
	3	23,158	−8.90	4.399
Speechiness	0	23,455	0.194	0.295
	1	23,333	0.096	0.170
	2	22,809	0.185	0.309
	3	23,158	0.059	0.067
Acousticness	0	23,455	0.814	0.291
	1	23,333	0.640	0.346
	2	22,809	0.493	0.309
	3	23,158	0.360	0.315
Instrumentalness	0	23,455	0.329	0.386
	1	23,333	0.213	0.347
	2	22,809	0.054	0.185
	3	23,158	0.058	0.189
Liveness	0	23,455	0.219	0.164
	1	23,333	0.229	0.194
	2	22,809	0.246	0.205
	3	23,158	0.189	0.162
Valence	0	23,455	0.523	0.265
	1	23,333	0.530	0.265
	2	22,809	0.580	0.249
	3	23,158	0.537	0.259

* Class: 0 = Unpopular, 1 = Low Popularity, 2 = Moderate Popularity, 3 = Highly Popular.