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
テレビショッピングがおかしい!!#陣内智則 #ネタジン #テレビショッピング #通信販売 #shorts
3M
Views
30.9K
Likes
176
Comments
Opportunity for growth
【芸歴29年 タケト大号泣のワケとは?!】控室は段ボール!!MCのはずがバイト扱い!!吉本退社を考えたあの日,,,
17.7K
Views
684
Likes
73
Comments
Analysis of 39 long-form videos
テレビショッピングがおかしい!!#陣内智則 #ネタジン #テレビショッピング #通信販売 #shorts
• Long videos make up 78% of total content
• Average performance: Lower than channel average
• Most common duration: Very Long (30+ min)
Upload patterns and optimal timing insights
Content distribution across 10 main categories
Key performance indicators and trends
Entertainment dominates with 42% of content
Television Program has highest avg views
Television Program shows strongest growth
Most used tags across 239 tag instances
15 tags in category
Comprehensive tag metrics and ROI analysis
| Tag | Usage | Avg Views | Engagement | Growth | ROI Score |
|---|---|---|---|---|---|
| #陣内智則Top 1 | 49 | 252.6K | 1.39% | -42% | 16/100 |
| #ネタ動画Top 2 | 49 | 252.6K | 1.39% | -42% | 16/100 |
| #芸人Top 3 | 49 | 252.6K | 1.39% | -42% | 16/100 |
| #よしもと | 49 | 252.6K | 1.39% | -42% | 16/100 |
| #コラボ | 9 | 107.5K | 2.88% | +15% | 30/100 |
| #steam | 5 | 71.9K | 1.74% | +40% | 18/100 |
| #呪物 | 4 | 155.9K | 3.28% | +13% | 34/100 |
| #田中俊行 | 4 | 155.9K | 3.28% | +13% | 34/100 |
| #タケト | 4 | 53.3K | 2.66% | +0% | 27/100 |
| #タケトのゾゾッとtown | 4 | 53.3K | 2.66% | +0% | 27/100 |
| #監視カメラ | 4 | 291.5K | 1.60% | +0% | 19/100 |
| #西田どらやき | 3 | 65.2K | 2.51% | +0% | 26/100 |
| #通販番組 | 2 | 2.2M | 1.06% | +0% | 33/100 |
| #テレビショッピング | 2 | 2.2M | 1.06% | +0% | 33/100 |
| #たっくーtvれいでぃお | 2 | 53.1K | 1.84% | +0% | 19/100 |
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