Contains aggregated temporal distributions of skip behavior, enabling
analysis of time-based patterns in user listening habits. This structure
captures how skip behavior varies across different time dimensions.
Properties:
hourlyDistribution: Skip counts for each hour of the day (0-23)
peakSkipHours: Array of hours with significantly high skip counts
dayOfWeekDistribution: Skip counts for each day of the week (0-6)
dayDistribution: Alternative day-based distribution
peakSkipDays: Array of days with significantly high skip counts
skipsByTimeOfDay: Categorized skips by time period (morning, afternoon, etc.)
This interface supports temporal pattern detection, including time-of-day
and day-of-week skip patterns that may reveal contextual listening habits.
Time-based skip distribution and pattern data
Contains aggregated temporal distributions of skip behavior, enabling analysis of time-based patterns in user listening habits. This structure captures how skip behavior varies across different time dimensions.
Properties:
This interface supports temporal pattern detection, including time-of-day and day-of-week skip patterns that may reveal contextual listening habits.