165,608
Followers
101
Following
2,449
Tweets
190.8
Avg Engagement
847
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @TitoRabat'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:2013-01-09
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:2,353
- Avg Likes per Tweet:146.6
- Avg Retweets per Tweet:44.2
- Followers Analyzed:50,000
Engagement Analysis
Based on 2,353 tweetsHis tweets receive a high number of likes and retweets, indicating strong audience interaction and interest in his content.
146.6
Avg Likes/Tweet
44.2
Avg Retweets/Tweet
344,949
Total Likes
104,110
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
98
Median Likes
19
Median Retweets
206
75th Percentile
11,358
Top Tweet
1.15
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Broadcaster
Primarily shares original content
78.3%
Original
7.7%
Replies
12.1%
Retweets
1.9%
Quotes
0.0%
Threads
0.3%
With Media
86.1%
With Links
52.0%
With #Tags
55.9%
With @Mentions
46.2%
With Emojis
116
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.1
Reply/Original Ratio
0.15
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
69.3%
Weekday Posts
30.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 2,353 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 285 retweets (12% 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 2,353 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 followersHis audience includes motorsport enthusiasts, fans of Ducati, and followers of MotoGP events.
Average
Audience Quality
33.5%
Suspicion Index
42.7%
Low-Quality %
7
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
53.1%
Empty Bio
45.2%
<10 Tweets
6.9%
Mass Following (>2K)
0.0%
New (<90 days)
73.8%
Low Ratio (<0.1)
0.0%
New (<180 days)
92.5%
No URL
32.3%
<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.
15,421,777
Total Potential Reach
7
Median Follower Reach
47
75th Percentile Reach
1.8%
>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).
32.7%
Creators
16,343 accounts
22.1%
Consumers
11,069 accounts
45.2%
Dormant
22,588 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):
73
Verified Followers
0.07% of total
8,264
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 |
|---|---|---|---|
| @MotoGP | 3,178,230 | Racing | Racing, Motorcycles, Speed |
| @SkySport | 2,973,771 | Sports Media | Sports, Teams, Passion |
| @SABreakingNews | 950,841 | News Outlet | News, South Africa, Breaking |
| @GettySport | 882,029 | Photographer | sports, photography, news |
| @djkingassassin | 472,145 | DJ | Music, Club, Producer |
| @wefollowbackd | 457,004 | Football Blogger | Football, News, Sport |
| @AleixEspargaro | 441,239 | MotoGP Rider | MotoGP, Rider, #41 |
| @DucatiMotor | 441,178 | Motorcycles | Motorcycles, Racing, Innovation |
| @Official_CS27 | 420,718 | Motorcyclist | Motorcycles, Fishing, Fatherhood |
| @OldPhotosBacon | 399,129 | Collector | Old Photos, Bacon, Amusing Stuff |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
42,073
Followers With Bio
58,924
Followers Without Bio
41.66%
% With Bio
58.34%
% 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 2,353 analyzed31,482
Combined Engagement
22,267
Total Likes
9,215
Total Retweets
6,296
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
60%
With Hashtags
20%
With @Mentions
80%
With Links
Topical Analysis:
¡Hola a todos! ¡Muchas gracias por los mensajes y todo el apoyo! Ya recuperándome y pensando en volver pronto a casa. Thank you very much for all your support. Already recovering and looking forward to go back home. #MotoGP #BritishGP #realeavintiaracing https://t.co/jc4PCxe45G
It's raceweek! ¡Y el cuerpo lo sabe! 🙃 #SanMarinoGP #MotoGP #ForzaDucati https://t.co/sj8rKwetZ7
World champion Moto2! Va por ti mama! QK❤️ http://t.co/f2xa6UfhV8
6 years without Marco Simoncelli. Always in our hearts! https://t.co/qdZH7nvvqR
RT @ValeYellow46: #buoncompleannosic
Key Insights & Takeaways
He frequently shares personal updates and gratitude towards his supporters, which helps build a loyal fanbase. He uses relevant hashtags and links to promote events and brands, enhancing visibility and engagement. His content often reflects his passion for racing and dedication to his sport, resonating with his audience.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 165,608
- + 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 @TitoRabat reveals an well-established Twitter presence with 165,608 followers. The account demonstrates a content-creator strategy, averaging 190.8 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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