Federica Pellegrini
Official Twitter: @mafaldina88 Official Instagram: KIKKAFEDE88
719,513
Followers
370
Following
11,481
Tweets
232.7
Avg Engagement
610
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @mafaldina88'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: Macro Influencer (100K+)
- Account Age:2013-04-05
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,234
- Avg Likes per Tweet:102.0
- Avg Retweets per Tweet:130.7
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,234 tweetsHer tweets receive high engagement, with an average of 8,322 likes and 658 retweets, indicating a highly interactive and supportive fan base.
102.0
Avg Likes/Tweet
130.7
Avg Retweets/Tweet
329,907
Total Likes
422,647
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
47
Median Likes
5
Median Retweets
126
75th Percentile
125,998
Top Tweet
0.32
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Mixed
Balanced content approach
57.1%
Original
4.2%
Replies
38.5%
Retweets
0.2%
Quotes
0.0%
Threads
0.2%
With Media
68.8%
With Links
46.3%
With #Tags
46.8%
With @Mentions
60.7%
With Emojis
111
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.07
Reply/Original Ratio
0.0
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
76.0%
Weekday Posts
24.0%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,234 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 1,245 retweets (38% 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 3,234 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 50,000 followersHer audience appears to be primarily interested in her personal journey and public recognition, with a strong presence in Italian-speaking communities.
Average
Audience Quality
33.5%
Suspicion Index
46.2%
Low-Quality %
7
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
55.8%
Empty Bio
48.1%
<10 Tweets
6.1%
Mass Following (>2K)
0.0%
New (<90 days)
69.4%
Low Ratio (<0.1)
0.0%
New (<180 days)
93.5%
No URL
36.7%
<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.
37,367,127
Total Potential Reach
7
Median Follower Reach
46
75th Percentile Reach
2.9%
>1K followers
0.3%
>10K followers
0.1%
>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).
33.1%
Creators
16,573 accounts
18.8%
Consumers
9,384 accounts
48.1%
Dormant
24,043 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):
148
Verified Followers
0.15% of total
5,265
Protected Accounts
5.21% of total
6 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 |
|---|---|---|---|
| @JohnCena | 14,105,204 | Wrestler | Wrestling, Motivation, Self-promotion |
| @matteorenzi | 3,379,723 | Politician | Politics, Italy, Florence |
| @miguelhotero | 1,928,581 | Journalist | Politics, Journalism, Leadership |
| @NicoSavi | 1,757,710 | Broadcaster | Lucca, Metanopoli, giovane old |
| @SinghLions | 1,335,042 | Restaurateur | Food, Travel, Influencer |
| @soledadobrien | 1,319,026 | Journalist | working, mom, journalist |
| @lodocomello | 1,131,466 | Entertainer | Music, Radio, Podcasts |
| @DeBortoliF | 661,261 | Journalist | journalism, news, media |
| @meb | 657,401 | Avvocato | Politica, Legge, Italia |
| @chetempochefa | 556,589 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
31,547
Followers With Bio
69,451
Followers Without Bio
31.24%
% With Bio
68.76%
% 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 3,234 analyzed248,352
Combined Engagement
28,746
Total Likes
219,606
Total Retweets
49,670
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
80%
With @Mentions
60%
With Links
Topical Analysis:
RT @rogerfederer: 🏆20. ❤️ https://t.co/WqUiSo3fd5
RT @TheOceanCleanup: According to our projections, we expect to be able to clean the entire Great Pacific Garbage Patch (containing 100,000…
RT @albertoangela: Buon viaggio papà. https://t.co/Rsu1CXXYV2
Grazie a tutti...veramente a tutti per i vostri messaggi di complimenti...è una cosa strana per me ...forse comincio a capire che non sto sulle palle proprio a tutti 🙏🏻🙏🏻😂😂😂😂 #graziegraziegrazie #fedefelice 🥰🥰
RT @Olympics: Olympic mode: engaged. 😎🔵🟡⚫🟢🔴 #EXO @weareoneEXO https://t.co/HaHpPIdEK2
Key Insights & Takeaways
She often shares personal milestones and gratitude, which resonates well with her audience. Her content is frequently linked to events like the Tokyo Aquatics Centre, suggesting a connection to sports or public events. She uses emojis and casual language, making her tweets more relatable and engaging.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 719,513
- + 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 @mafaldina88 reveals an well-established Twitter presence with 719,513 followers. The account demonstrates a content-creator strategy, averaging 232.7 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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