Paolo De Ceglie
Calciatore professionista
104,446
Followers
77
Following
842
Tweets
73.0
Avg Engagement
959
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @paolo_deceglie'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:2010-09-06
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:812
- Avg Likes per Tweet:21.2
- Avg Retweets per Tweet:51.8
- Followers Analyzed:10,000
Engagement Analysis
Based on 812 tweetsHis tweets receive an average of 471 likes and 597 retweets, indicating a highly engaged and supportive fan base.
21.2
Avg Likes/Tweet
51.8
Avg Retweets/Tweet
17,210
Total Likes
42,071
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
5
Median Likes
8
Median Retweets
49
75th Percentile
5,719
Top Tweet
0.7
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Curator
Amplifies others content frequently
55.8%
Original
1.1%
Replies
43.0%
Retweets
0.1%
Quotes
0.0%
Threads
1.5%
With Media
59.2%
With Links
52.1%
With #Tags
57.0%
With @Mentions
3.6%
With Emojis
106
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.02
Reply/Original Ratio
0.0
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
82.9%
Weekday Posts
17.1%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 812 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 349 retweets (43% 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 812 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 10,000 followersHis audience likely includes football fans, fellow players, and sports enthusiasts interested in his career and achievements.
Average
Audience Quality
33.1%
Suspicion Index
32.8%
Low-Quality %
26
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
45.6%
Empty Bio
34.6%
<10 Tweets
19.2%
Mass Following (>2K)
0.0%
New (<90 days)
74.2%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.6%
No URL
20.0%
<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.
3,741,197
Total Potential Reach
26
Median Follower Reach
108
75th Percentile Reach
3.1%
>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).
36.8%
Creators
3,677 accounts
28.6%
Consumers
2,858 accounts
34.6%
Dormant
3,465 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):
7
Verified Followers
0.07% of total
818
Protected Accounts
8.18% of total
7 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 |
|---|---|---|---|
| @wefollowbackd | 456,540 | Football Blogger | Football, News, Sport |
| @CB_Ignoranza | 271,902 | Footballer | Calcio, Umorismo, Spogliatoio |
| @scormix | 153,552 | Animal rights activist | Animal rights, Equality, Respect |
| @PauloRafael | 141,927 | Operador de Produção | Chemistry, Production, 90's |
| @lemutuz_brand | 103,641 | - | - |
| @TheSportsman | 101,698 | Sports Media | Sports, Fans, Community |
| @TBS_SuperSoccer | 95,452 | Sports Broadcaster | soccer, sports, TV |
| @deysibenitez_01 | 87,566 | Influencer | Julián Daher, love, life |
| @Tarhuna69 | 84,192 | Influencer | Libyan, Proud, Tarhuna |
| @JuanSGE | 81,429 | Influencer | Light, Love, Team |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
5,443
Followers With Bio
4,557
Followers Without Bio
54.43%
% With Bio
45.57%
% 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 812 analyzed15,285
Combined Engagement
1,774
Total Likes
13,511
Total Retweets
3,057
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
60%
With Hashtags
60%
With @Mentions
100%
With Links
Topical Analysis:
RT @ChampionsLeague: We'll light up the Brandenburg Gate in @juventusfc colours at 10.30/10.45 tonight if we pass 5k retweets! #UCLfinal http://t.co/4Od1fAVc5X
RT @juventusfc: FULL-TIME: Il primo round è nostro!!!! BIANCONERI STREPITOSI!!! #JuveReal 2-1 #FinoAllaFinale http://t.co/uWvBUxyMUm
RT @juventusfc: #Camp10ni http://t.co/SAP4ADQIHQ
Andiamo a Berlino!!!!!!! http://t.co/GO4wewwqai
Grandissimi!!! http://t.co/9GrC69fOlP
Key Insights & Takeaways
His top tweets focus on major football events and team successes, suggesting a strong connection to his club and fan community. He uses hashtags and links to promote team spirit and fan engagement. His verified status is low, which may indicate a personal rather than corporate account.
Strengths
- + Established follower base of 104,446
- + 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 @paolo_deceglie reveals an growing Twitter presence with 104,446 followers. The account demonstrates a content-creator strategy, averaging 73.0 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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