Retrieves the top skipped artists based on skip count and percentage
Analyzes the artist-level skip statistics across the entire listening history
and returns a list of artists whose tracks are skipped most frequently. This
function helps identify potential patterns in artist preferences and listening
behavior.
The analysis includes:
Total skip count for each artist's tracks
Skip percentage (skips relative to total plays)
Number of tracks played for each artist
Sorting by skip frequency with percentage as a secondary factor
This data is useful for understanding which artists' music the user tends
to skip more frequently, which may indicate changing music preferences or
context-dependent listening patterns.
Example
// Display the top 3 most frequently skipped artists consttopSkippedArtists = awaitgetTopSkippedArtists(3); renderArtistSkipChart(topSkippedArtists);
// Group tracks by artist and calculate aggregate statistics constartistStats: Record< string, { id: string; name: string; skipCount: number; trackCount: number; totalTracks: number; } > = {};
// Process track metrics to aggregate by artist Object.values(statistics.trackMetrics).forEach((track) => { constartistId = track.id.split(":")[0] || "unknown"; // Generate an ID if we don't have one constartistName = track.artistName || "Unknown Artist";
Retrieves the top skipped artists based on skip count and percentage
Analyzes the artist-level skip statistics across the entire listening history and returns a list of artists whose tracks are skipped most frequently. This function helps identify potential patterns in artist preferences and listening behavior.
The analysis includes:
This data is useful for understanding which artists' music the user tends to skip more frequently, which may indicate changing music preferences or context-dependent listening patterns.
Example
Source