General and Entertainment ranking performance
General
Global
Japan
Entertainment
Global
Japan
Total Videos
Content Library
Total Views
Lifetime Views
Subscribers
Community Size
Engagement Rate
Audience Interaction
Top performer by views
【要約】ハーバード、スタンフォード、科学的に証明された時間をムダにしない人の習慣【堀田 秀吾】
191.3K
Views
3.3K
Likes
101
Comments
Opportunity for growth
【要約】フランス人は10着しか服を持たない【ジェニファー・L・スコット (著), 神崎朗子 (翻訳)】
15.5K
Views
347
Likes
27
Comments
Analysis of 50 long-form videos
【要約】ハーバード、スタンフォード、科学的に証明された時間をムダにしない人の習慣【堀田 秀吾】
• Long videos make up 100% of total content
• Average performance: Better than channel average
• Most common duration: Long (10-30 min)
Upload patterns and optimal timing insights
More Shorts are needed for analysis.
Content distribution across 3 main categories
Key performance indicators and trends
Entertainment dominates with 88% of content
Society has highest avg views
Entertainment shows strongest growth
Most used tags across 748 tag instances
15 tags in category
Comprehensive tag metrics and ROI analysis
| Tag | Usage | Avg Views | Engagement | Growth | ROI Score |
|---|---|---|---|---|---|
| #フェルミ大学Top 1 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #書籍Top 2 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #要約Top 3 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #漫画 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #マンガ | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #マンガでわかる | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #中田敦彦 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #youtube大学 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #勉強 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #フェルミ漫画大学 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #まとめ | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #本要約 | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #本まとめ | 50 | 60.9K | 2.31% | +7% | 24/100 |
| #わかりやすい | 49 | 61.4K | 2.31% | +6% | 24/100 |
| #わかりやすく | 49 | 61.4K | 2.31% | +6% | 24/100 |
Strategic recommendations and performance highlights
Top 5 by view count





Top 5 by like count





Top 5 by comment count





Top 5 by engagement rate





Peak performance metrics across all categories
Top performers across multiple categories



Performance analysis and recommendations