598,668
Followers
872
Following
18,067
Tweets
300.7
Avg Engagement
1,170
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @PIERPARDO'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:2011-03-28
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,247
- Avg Likes per Tweet:173.9
- Avg Retweets per Tweet:126.8
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,247 tweetsPIERPARDO's tweets receive strong engagement, with an average of 5,014 likes and 552 retweets per post. Their content resonates well with their followers.
173.9
Avg Likes/Tweet
126.8
Avg Retweets/Tweet
564,631
Total Likes
411,678
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
48
Median Likes
4
Median Retweets
188
75th Percentile
98,260
Top Tweet
0.5
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
57.3%
Original
15.7%
Replies
8.7%
Retweets
18.3%
Quotes
0.0%
Threads
0.0%
With Media
40.8%
With Links
68.9%
With #Tags
59.2%
With @Mentions
3.0%
With Emojis
121
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.27
Reply/Original Ratio
2.1
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
73.1%
Weekday Posts
26.9%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,247 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 283 retweets (9% 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 3,247 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 followersThe audience likely includes Italian sports fans and followers of emotional, nostalgic content. They are engaged with themes of national pride and sports history.
Average
Audience Quality
34.6%
Suspicion Index
45.1%
Low-Quality %
5
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
53.6%
Empty Bio
49.1%
<10 Tweets
6.6%
Mass Following (>2K)
0.0%
New (<90 days)
74.6%
Low Ratio (<0.1)
0.0%
New (<180 days)
94.7%
No URL
36.6%
<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.
27,996,252
Total Potential Reach
5
Median Follower Reach
35
75th Percentile Reach
2.0%
>1K followers
0.2%
>10K followers
0.1%
>50K followers
0.0%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
29.6%
Creators
14,796 accounts
21.3%
Consumers
10,653 accounts
49.1%
Dormant
24,551 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):
192
Verified Followers
0.19% of total
5,263
Protected Accounts
5.21% 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 |
|---|---|---|---|
| @JohnCena | 14,105,289 | Wrestler | Wrestling, Motivation, Self-promotion |
| @matteorenzi | 3,379,650 | Politician | Politics, Italy, Florence |
| @wanditanara | 2,873,087 | Influencer | Fashion, Beauty, Lifestyle |
| @beppesevergnini | 1,127,659 | Journalist | Travel, Culture, Humor |
| @Azzurri | 933,257 | Football Team | Calcio, Nazionale, Azzurri |
| @RudyZerbi | 931,497 | Musician | Music, Television, Personality |
| @FabioDeLuigi | 905,814 | Actor | Comedy, Acting, Entertainment |
| @OfficialMonto | 845,633 | Footballer | Football, Sports, Sponsorship |
| @ZachBoychuk | 829,869 | Hockey Player | Hockey, Meme/NFT Trading, Ethereum |
| @antoclerici | 753,333 | Journalist | Giornalismo, Televisione, Famiglia |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
42,371
Followers With Bio
58,627
Followers Without Bio
41.95%
% With Bio
58.05%
% 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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Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,247 analyzed308,092
Combined Engagement
0
Total Likes
308,092
Total Retweets
61,618
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
100%
With @Mentions
40%
With Links
Topical Analysis:
RT @Tito9k9: Un padre de 88 años de edad se reencuentra con su hijo de 53 años que tiene síndrome de Down después de pasar una semana separ…
RT @ManCity: https://t.co/Kz89wXt8It
RT @rogerfederer: Apparently I'm the oldest tennis player with a #1️⃣ ranking. Somebody might have mentioned that to me already but I had a…
RT @JoelEmbiid: Man I don’t even know where to start😭😭 I started playing ball because of KOBE after watching the 2010 finals. I had never w…
RT @BBCSport: One Bradley Lowery. https://t.co/murlri9E0X
Key Insights & Takeaways
Their top tweets often reference iconic moments in Italian sports history, which likely drive high engagement. They use hashtags to amplify their reach and connect with broader audiences. Their content is emotionally charged, focusing on nostalgia and national pride.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 598,668
- + 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 @PIERPARDO reveals an well-established Twitter presence with 598,668 followers. The account demonstrates a content-creator strategy, averaging 300.7 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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