We constructed a dataset with approximately 1.8 million hit and non-hit songs and extracted their audio features using the Spotify Web API. This dataset can be used to make a classification model that predicts whether a track would be a 'Hit' or not. Audio features extracted from Spotify’s API. Thanks to the Spotify Hit Predictor set on Kaggle . It actually allows users to monetize the playlists that they have on Apple Music or Spotify. Energy — The energy of a song — the higher the value, the more energetic the song. In this work, we attempt to solve the Hit Song Science problem, which aims to predict which songs will become chart-topping hits. Context: This is a dataset consisting of features for tracks fetched using Spotify's Web API. YOU can make an important difference in the music and influence record companies, radio stations, managers, today\'s biggest artists and new up & coming artists. Table 1. In their study, pre-published on arXiv, they trained four models on song-related data extracted using the Spotify Web API, and then evaluated their performance in predicting what songs would become hits. This platform also connects music artists with playlist creators on different music platforms and apps. HitPredictor gives you the power to directly influence new music before it\'s released to the public. LR and NN give the highest prediction accuracy on the validation set. Billboard hit prediction accuracy results for five machine-learning algorithms. The Spotify Hit Predictor Dataset (1960-2019) Over 40,000+ Tracks labeled hit or flop, with their features. Billboard Hot 100 Hit Prediction Predicting Billboard's Year-End Hot 100 Songs using audio features from Spotify and lyrics from Musixmatch Overview. Joined with Genre of songs that isn't available on only the hit predictor dataset from 1960 to 2010's. Inspiration. Acknowledgements. BPM — Beats per minute. Failed to retrieve activity summary data. In this work, we attempt to solve the Hit Song Science problem, which aims to predict which songs will become chart-topping hits. Farooq Ansari • updated 10 months ago (Version 2) Data Tasks Code (7) Discussion (1) Activity Metadata. Each year, Billboard publishes its Year-End Hot 100 songs list, which denotes the top 100 songs of that year. more_vert. 1. The tempo of the song. 3. The tracks are labeled '1' or '0' ('Hit' or 'Flop') depending on some criterias of the author. Download (3 MB) New Notebook. Understanding and Expanding creativity Music artists can also pitch their songs directly to the playlist creators through this app. … Content. Spotify assigns each song a value between 0 and 1 for these features, except loudness which is measured in decibels. Over 40,000+ Tracks labeled hit or flop, with their features. Two students and researchers at the University of San Francisco (USF) have recently tried to predict billboard hits using machine-learning models. Our best model was random forest, which was able to predict Billboard song success with … 2. We constructed a dataset with approximately 1.8 million hit and non-hit songs and extracted their audio features using the Spotify Web API. Spotify Hit Predictor Dataset used for supervised ML . We test four models on our dataset. We test four models on our dataset.