mlsanityData to 7 Oct 2026

SpotHitPy: A Study For ML-Based Song Hit Prediction Using Spotify

arXiv 2301.07978 ↗First posted 19 Jan 2023cs.SD cs.LG eess.AScited by 2

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Abstract (arXiv)

In this study, we approached the Hit Song Prediction problem, which aims to predict which songs will become Billboard hits. We gathered a dataset of nearly 18500 hit and non-hit songs and extracted their audio features using the Spotify Web API. We test four machine-learning models on our dataset. We were able to predict the Billboard success of a song with approximately 86% accuracy. The most succesful algorithms were Random Forest and Support Vector Machine.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 2 of its 10 references that are in the map. First posted on arXiv 19 Jan 2023.

Builds on

2 of 10 references.

References · 2

  1. 2017Revisiting the problem of audio-based hit song prediction using convolutional neural networkscited by 4
  2. 2019Song Hit Prediction: Predicting Billboard Hits Using Spotify Datacited by 4

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Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2024Beyond Beats: A Recipe to Song Popularity? A machine learning approachcited by 2
  2. 2025Beyond the Hook: Predicting Billboard Hot 100 Chart Inclusion with Machine Learning from Streaming, Audio Signals, and Perceptual Featurescited by 0