Ivana Ferreira Fuso
Brasileira 🇧🇷 Footballer for @manutdwomen : Managment ✍🏼:@sportstransferwomen @sportstransfer Salmos91✨
18,342
Followers
60
Following
313
Tweets
382.9
Avg Engagement
49
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Ivana_FFuso's Twitter/X presence across multiple dimensions. We analyze tweet content, engagement patterns, audience demographics, posting habits, and network connections to provide actionable insights about this account's social media strategy and influence.
Account Classification
- Account Size: Mid-Tier (10K+)
- Account Age:2020-09-07
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:295
- Avg Likes per Tweet:348.1
- Avg Retweets per Tweet:34.8
- Followers Analyzed:16,085
Engagement Analysis
Based on 295 tweetsHer tweets receive an average of 1,695 likes and 91 retweets, indicating a moderately engaged audience.
348.1
Avg Likes/Tweet
34.8
Avg Retweets/Tweet
102,699
Total Likes
10,258
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
231
Median Likes
18
Median Retweets
550
75th Percentile
2,781
Top Tweet
20.88
Engagement per 1K Followers
Normalized influence metric
Long Tail
Engagement Pattern
Mix of hits and regular posts
Posting Behavior
Content style and format preferences
Mixed
Balanced content approach
44.4%
Original
18.6%
Replies
18.3%
Retweets
18.6%
Quotes
0.0%
Threads
0.0%
With Media
72.5%
With Links
31.5%
With #Tags
41.0%
With @Mentions
89.5%
With Emojis
105
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.42
Reply/Original Ratio
1.02
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
72.2%
Weekday Posts
27.8%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 295 tweetsContent Type Distribution
Content Breakdown
What This Reveals About Their Strategy
This is a content-creator focused account that primarily shares original thoughts, ideas, and media. With original content dominating their feed, they position themselves as a source of new information rather than a curator. This strategy works well for establishing thought leadership.
The 54 retweets (18% of activity) show they also amplify content from others, which helps build relationships with other accounts and provides value to followers by surfacing relevant content.
Posting Patterns & Optimal Timing
Based on 295 tweetsEngagement by Hour (UTC)
Posting Frequency Over Time
Timing Insights
Understanding when an account posts and when their audience is most responsive provides valuable competitive intelligence. The charts above show when this account's content receives the most engagement, which often correlates with when their specific audience is most active on the platform.
Peak posting times vary significantly based on an account's audience demographics, timezone distribution, and content type. Accounts with global audiences often see engagement spread across multiple time windows, while those with regional focus may have more concentrated peaks.
Audience Demographics
Based on 16,085 followersHer followers likely include football fans, fellow athletes, and sports enthusiasts interested in her career and personal life.
Average
Audience Quality
23.4%
Suspicion Index
20.6%
Low-Quality %
82
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
30.3%
Empty Bio
18.3%
<10 Tweets
22.1%
Mass Following (>2K)
0.0%
New (<90 days)
50.7%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.6%
No URL
10.9%
<3 Tweets
Free Mode Analysis: These quality metrics use heuristic signals (empty bios, low tweets, suspicious ratios). For ML-powered bot detection with 95%+ accuracy, use our dedicated tool.
Try Bot DetectorFollower Reach & Influence
This account's followers have their own audiences, creating potential for secondary amplification.
51,431,984
Total Potential Reach
82
Median Follower Reach
299
75th Percentile Reach
9.0%
>1K followers
0.8%
>10K followers
0.2%
>50K followers
0.1%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
61.7%
Creators
9,930 accounts
19.9%
Consumers
3,206 accounts
18.3%
Dormant
2,949 accounts
Follower Influence Distribution
How many followers do their followers have?
Follower Account Age
How long have followers been on Twitter?
Geographic Distribution
Top locations where followers are based (from those who share location data):
98
Verified Followers
0.61% of total
1,449
Protected Accounts
9.01% of total
5 years
Avg Account Age
of their followers
Notable Followers (By Influence)
Top accounts following this user, sorted by their follower count:
| Username | Followers | Profession | Interests |
|---|---|---|---|
| @ManUtd | 35,590,625 | Sports Team | Football, Manchester, United |
| @UnitedStandMUFC | 1,913,234 | Fan Channel | Manchester United, Global Fanbase, Latest News |
| @ManUtdMEN | 1,618,408 | Sports Journalist | Football, Manchester United, News |
| @Moreno | 430,153 | Influencer | Business, Manager, Serious |
| @ManUtdWomen | 388,387 | Sports Team | Football, Women's sports, Activism |
| @MU_Foundation | 384,046 | Charity | Football, Charity, Young People |
| @CalumBest | 372,549 | Entrepreneur | Mindfulness, Entrepreneurship, Fitness |
| @ManUtd_MY | 315,926 | Football Club | Football, Manchester United, Bahasa Malaysia |
| @Richard7Hill | 288,821 | Football Fan | ManUtd, Snooker, England |
| @BarclaysWSL | 275,806 | Football | Women's football, England, Top-flight |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
11,207
Followers With Bio
4,878
Followers Without Bio
69.67%
% With Bio
30.33%
% Without Bio
Why Audience Demographics Matter
Understanding who follows an account reveals the type of influence they hold. Accounts followed primarily by users with few followers indicate broad, mainstream appeal. Those with many high-follower followers have greater potential for content amplification through secondary sharing.
Account age distribution also tells a story: a follower base with many new accounts might indicate recent viral growth, while established followers suggest long-term, stable influence. Geographic data helps understand the cultural context and timezone spread of the audience.
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Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 295 analyzed10,245
Combined Engagement
9,749
Total Likes
496
Total Retweets
2,049
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
20%
With @Mentions
100%
With Links
Topical Analysis:
Too hot to handle 😮💨☀️🤪 https://t.co/6Ww4w9fj2y
Meu Deus 🤩🤩 Vamosss🔥 https://t.co/pBPSef6Avl
It’s OK if you don’t like me because not everyone has good taste.😉 https://t.co/bnoekk7e3p
That’s my bestieee😍🫶🏽 @OnaBatlle https://t.co/oqKVu3lQvu
Deus sabe de todas as coisas… https://t.co/YexVsP1Fv1
Key Insights & Takeaways
She blends personal humor with professional content, which helps build a relatable image. Her use of emojis and casual language makes her tweets more approachable and engaging. She leverages her verified accounts for sports transfers, suggesting a focus on career development and networking.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 18,342
- + Strong original content creation
- + Active presence with consistent posting
Opportunities
- ~ Optimize posting times for peak engagement windows
- ~ Analyze top-performing content for replicable patterns
- ~ Leverage geographic concentration for targeted content
- ~ Explore collaboration potential with followed accounts
Summary
This analysis of @Ivana_FFuso reveals an well-established Twitter presence with 18,342 followers. The account demonstrates a content-creator strategy, averaging 382.9 engagements per tweet. Key strengths include consistent posting and an engaged audience, with opportunities to further optimize timing and content strategy based on the patterns identified in this report.
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