NaNa说美股
@nanashuomeigu
1.6K
Video Count95.7M
Video View307.0K
Subscriber#2,368
France Rank#95,182
Global RankGeneral and Education ranking performance
General
Global
France
Education
Global
France
Total Videos
Content Library
Total Views
Lifetime Views
Subscribers
Community Size
Engagement Rate
Audience Interaction
Top performer by views
要俯冲脸着地了！NaNa说美股(2026.03.18)
97.4K
Views
3.9K
Likes
203
Comments
Opportunity for growth
咋了，伊朗反攻华盛顿了？？NaNa说美股(2026.03.06)
23.9K
Views
2K
Likes
146
Comments
Analysis of 50 long-form videos
要俯冲脸着地了！NaNa说美股(2026.03.18)
• 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 1 main categories
Key performance indicators and trends
Society dominates with 100% of content
Society has highest avg views
Society shows strongest growth
Most used tags across 750 tag instances
15 tags in category
Comprehensive tag metrics and ROI analysis
| Tag | Usage | Avg Views | Engagement | Growth | ROI Score |
|---|---|---|---|---|---|
| #美股崩盘Top 1 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #做空美股Top 2 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #美国股市大盘Top 3 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #美股 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #美国股市 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #美股大盘 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #美股空头 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #大盘 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #割韭菜 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #财经 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #金融 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #金融危机 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #美国经济 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #期权 | 50 | 47.5K | 6.38% | +70% | 64/100 |
| #股票 | 50 | 47.5K | 6.38% | +70% | 64/100 |
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