161,514
Followers
717
Following
11,238
Tweets
956.5
Avg Engagement
707
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @monstatrezz'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:2010-04-16
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,223
- Avg Likes per Tweet:549.9
- Avg Retweets per Tweet:406.6
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,223 tweetsTheir tweets receive high engagement, with an average of 27,340 likes and 2,999 retweets per post.
549.9
Avg Likes/Tweet
406.6
Avg Retweets/Tweet
1,772,314
Total Likes
1,310,478
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
25
Median Likes
7
Median Retweets
281
75th Percentile
355,921
Top Tweet
5.92
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Commentator
Adds perspective to others content
31.8%
Original
23.0%
Replies
24.1%
Retweets
21.2%
Quotes
0.0%
Threads
0.3%
With Media
41.8%
With Links
10.4%
With #Tags
53.1%
With @Mentions
28.5%
With Emojis
74
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.72
Reply/Original Ratio
0.88
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
69.8%
Weekday Posts
30.2%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,223 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 776 retweets (24% 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 3,223 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 followersTheir audience appears to be interested in personal stories, sports, and cultural commentary.
Average
Audience Quality
28.2%
Suspicion Index
31.3%
Low-Quality %
21
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
41.1%
Empty Bio
31.9%
<10 Tweets
10.2%
Mass Following (>2K)
0.0%
New (<90 days)
67.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
91.2%
No URL
21.6%
<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.
57,958,554
Total Potential Reach
21
Median Follower Reach
119
75th Percentile Reach
3.7%
>1K followers
0.4%
>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).
47.5%
Creators
23,775 accounts
20.6%
Consumers
10,293 accounts
31.9%
Dormant
15,932 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):
485
Verified Followers
0.48% of total
12,243
Protected Accounts
12.12% 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 | 14,100,530 | Wrestler | Wrestling, Motivation, Self-promotion |
| @AdamSchefter | 10,338,702 | Sports Journalist | NFL, Insider, Podcast |
| @robkardashian | 7,089,296 | Celebrity | Family, Fitness, Fashion |
| @Wale | 6,217,746 | Writer | anti-hero, super genius, music |
| @andreolifelipe | 3,351,700 | Jornalista | Esportes, Jornalismo, Globo |
| @sixers | 2,316,282 | Sports Team | basketball, Philadelphia, riffin' |
| @adinross | 2,251,482 | Content Creator | Twitch, YouTube, Business |
| @isaiahthomas | 1,872,900 | Basketball Player | Basketball, Fatherhood, All Star |
| @JalenRose | 1,803,023 | Analyst | Basketball, Education, Media |
| @JASMINEVILLEGAS | 1,544,412 | Singer | Music, Dreaming, Life |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
61,948
Followers With Bio
39,044
Followers Without Bio
61.34%
% With Bio
38.66%
% 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 3,223 analyzed733,665
Combined Engagement
133,140
Total Likes
600,525
Total Retweets
146,733
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
60%
With @Mentions
80%
With Links
Topical Analysis:
RT @lkigai_: The middle guy is how balanced I want my life to be https://t.co/FDMbH6igwV
RT @JColeNC: KOD 4/20 Cover and back https://t.co/2iUaKrI42F
If gone get the story get it right all I ask, no one spoke wit me to do anything I approach him and cleared the air from all the outside nonsense that was being said. Nothing but respect for Luka he understood the heat of the battle and he said it didn’t bother him only RESPECT h
Much respect cuh 2-2 let’s enjoy the rest #PlayoffBasketball https://t.co/MnkVpEN5Bf
RT @armon_bell: DABABY ATE THIS🔥🔥🔥🔥 https://t.co/defTKmb2wM
Key Insights & Takeaways
They often share deeply personal stories, which resonate strongly with their audience. Their content includes references to sports figures and cultural icons, indicating a niche interest. They maintain a consistent posting schedule, which likely contributes to their high engagement rates.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 161,514
- + 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 @monstatrezz reveals an well-established Twitter presence with 161,514 followers. The account demonstrates a content-creator strategy, averaging 956.5 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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