Predict what makes a song hit
Exploring the intricate elements that make a song successful on Spotify. By analyzing audio features and listener data, this work aims to decode the complex interplay between musical elements and listener preferences, thus providing actionable insights for music industry stakeholders.
The primary objective of this project is to uncover the key musical elements and listener preferences that contribute to a song's success in today's digital era of music streaming. Through comprehensive data analysis, the project seeks to identify trends and patterns that could help music producers, artists, and record labels optimize their outputs to meet listener expectations effectively.
LINK: https://onyxdata.co.uk/data-dna-dataset-challenge/datadna-dataset-archive/
The dataset utilized in our project, "Spotify Most Streamed Songs 2023 Dataset - October 2023", was sourced from Onyx Data's DataDNA Dataset Challenge. It provides a comprehensive view of the audio features and listener engagement metrics for the most streamed songs on Spotify as of October 2023. This dataset allows us to delve into the specifics of what attributes contribute to a song's success on one of the world's largest music streaming platforms.
The dataset comprises several key features, each offering insights into different aspects of musical compositions and listener preferences:
- Track ID and Name: Unique identifiers for each song along with their titles provide a basis for detailed track-level analysis.
- Artist Name: This helps in assessing the impact of artist popularity on streaming numbers.
- Audio Features:
- Acousticness: A measure indicating the presence of acoustic sounds in a track.
- Danceability: Describes how suitable a track is for dancing based on tempo, rhythm stability, beat strength, and overall regularity.
- Energy: A measure of intensity and activity, often derived from dynamics and volume.
- Valence: Measures the musical positiveness conveyed by a track.
- Tempo: The overall estimated tempo of a song, measured in beats per minute (BPM).
- Popularity: A metric that combines listening data and plays counts over recent periods to gauge how popular a song is among listeners.
The analysis revealed several key insights:
- Musical Attributes: There's a noticeable shift towards songs with higher danceability and energy, while acousticness has declined, indicating a trend towards more synthesized, beat-driven music.
- Tempo Analysis: A significant finding was that the optimal tempo for a hit song tends to hover around 120 BPM, which aligns closely with the human heartbeat during moderate activity, making these songs more engaging and easier to dance to.
- Key Dominance: The study noted shifts in key preferences over time, with certain keys like C# Major and D Major becoming more popular in recent decades, which may influence how songs are composed.
- Artist Name Impact: The analysis also explored whether an artist’s name affects their popularity on Spotify, concluding that while an interesting name might capture initial attention, it is the musical quality that sustains listener interest and engagement.