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Fantano Review Data with Spotify Metrics
Data Science and Analytics
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Free
About
This data product contains a detailed collection of album reviews generated by the popular YouTube music critic Anthony Fantano, who operates the needledrop channel, spanning the years 2010 through 2022. It brings together core information from the review videos, such as the artist, project title, and the final 0-10 review score, and enriches this content with technical musical attributes extracted via Spotify. These additional attributes include the number of tracks, project duration, and specific song characteristics like key, mode, and danceability. Data was gathered using the YouTube and Spotify APIs. Future iterations of this product are expected to incorporate lyrical data from Genius and transcribed free-text content of the reviews.
Columns
The dataset includes 10 distinct columns:
- Index of the album: An internal positional indicator for the records, with a maximum value of 3023.
- spotify_id: The unique Spotify identifier for the reviewed album; this field may occasionally be null if the project is not listed on Spotify.
- youtube_id: The specific video ID corresponding to the review on YouTube.
- project_name: The title or name of the reviewed musical work.
- artist: The performer or group responsible for the musical project.
- project_type: Defines the format of the project being reviewed, with 'album' being the most common category (90%), followed by 'ep'.
- tracks: The count of individual songs associated with the project, as sourced from Spotify.
- project_art: A direct URL link to the official album artwork.
- year: The year during which the review was published.
- rating: The critical score assigned to the project, based on a 0-10 point scale, with the mean rating being 6.23.
Distribution
The data is supplied in a CSV file format, specifically
albums.csv. The structure contains 3,024 valid records across all primary fields. The usability score for this data stands at 10.00. Updates to this data product are projected to occur on a quarterly basis.Usage
This data is ideal for quantitative analysis linking subjective music criticism to objective audio characteristics. Researchers can study the correlation between a reviewer’s rating (0-10 scale) and technical attributes (like danceability or mode). It supports trend analysis in music criticism over the 2010-2022 period and is suitable for training machine learning models designed to predict critical success based on musical features.
Coverage
The review period spans over a decade, covering projects reviewed between 2010 and 2022. The content primarily focuses on albums (90%) but also includes EPs and other project types. It features reviews of over 1,400 unique artists.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For developing predictive models in the arts and entertainment space or performing sentiment analysis against musical traits.
- Academic Researchers: To investigate patterns in music critical reception, media influence, and the impact of digital media reviewers.
- Music Analysts: Individuals or organisations seeking insight into which musical features tend to correlate with higher or lower critical scores.
Dataset Name Suggestions
- Fantano Review Data with Spotify Metrics
- needledrop Album Scores (2010-2022)
- Music Review and Audio Feature Dataset
Attributes
Original Data Source: Fantano Review Data with Spotify Metrics
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