DeMarvin Leal
Steelers.
21764
Followers
3874
Following
5573
Tweets
4906,6
Avg Engagement
82
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @boimarv9'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: Mid-Tier (10K+)
- Account Age:2016-06-12
- Verification:No
- Location:Pittsburgh, PA
Data Summary
- Tweets Analyzed:3029
- Avg Likes per Tweet:65,7
- Avg Retweets per Tweet:4840,9
- Followers Analyzed:21717
Engagement Analysis
Based on 3029 tweetsThe account shows high engagement with an average of 4,201 likes per tweet, suggesting a loyal and active fan base. Retweets are also relatively frequent, indicating community interaction.
65,7
Avg Likes/Tweet
4840,9
Avg Retweets/Tweet
199048
Total Likes
14662958
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
20
Median Retweets
1425
75th Percentile
385564
Top Tweet
225,44
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
12,3%
Original
2,7%
Replies
64,7%
Retweets
20,3%
Quotes
0,0%
Threads
0,2%
With Media
63,0%
With Links
14,6%
With #Tags
69,5%
With @Mentions
43,9%
With Emojis
82
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0,22
Reply/Original Ratio
0,31
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
71,4%
Weekday Posts
28,6%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3029 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 1960 retweets (65% 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 3029 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 21717 followersThe audience primarily consists of Steelers fans, as indicated by the bio and top tweets. The user's content is likely shared within a dedicated fan community.
Good
Audience Quality
15,9%
Suspicion Index
19,2%
Low-Quality %
123
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
33,3%
Empty Bio
8,7%
<10 Tweets
14,1%
Mass Following (>2K)
0,0%
New (<90 days)
32,4%
Low Ratio (<0.1)
0,0%
New (<180 days)
86,4%
No URL
5,0%
<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.
71762299
Total Potential Reach
123
Median Follower Reach
381
75th Percentile Reach
10,8%
>1K followers
1,9%
>10K followers
0,5%
>50K followers
0,3%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
77,5%
Creators
16835 accounts
13,8%
Consumers
3000 accounts
8,7%
Dormant
1882 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):
269
Verified Followers
1.24% of total
2377
Protected Accounts
10.95% of total
8 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 | 14106717 | Wrestler | Wrestling, Motivation, Self-promotion |
| @verified | 4201287 | - | - |
| @steelers | 3751050 | Sports Team | football, champions, Pittsburgh |
| @NFLonFOX | 3642351 | Sports Media | Football, NFL, Sports |
| @MichaelVick | 2618505 | NFL Analyst | NFL, Analyst, Sports |
| @6BillionPeople | 2038886 | - | - |
| @JManziel2 | 1894141 | Athlete | Football, Good vibes |
| @KameronBennett | 1810194 | DJ | Music, DJing, Booking |
| @MurrayNewlands | 1521873 | Contributor | pop art, art, entrepreneurship |
| @SinghLions | 1336527 | Restaurateur | Food, Travel, Influencer |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
14484
Followers With Bio
7233
Followers Without Bio
66.69%
% With Bio
33.31%
% 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 3029 analyzed1409895
Combined Engagement
0
Total Likes
1409895
Total Retweets
281979
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
100%
With @Mentions
100%
With Links
Topical Analysis:
RT @_dlew32: I cant afford a gym membership so 😂 https://t.co/uyteBC6s5m
RT @BarackObama: In every scene, you are my star, @MichelleObama! Happy birthday, baby! https://t.co/hgMBhHasBj
RT @KevOnStage: I don't usually yell at my kids. But he deserved it. https://t.co/0Bo9Hsecvx
RT @VancityReynolds: I’ve waited my whole life for this. https://t.co/mVWUioY2F8
RT @rileykennedyyy: rt in 5 secs or bad luck will happen https://t.co/Qo751zvr0g
Key Insights & Takeaways
The user is heavily focused on Steelers-related content, which drives engagement. The top tweets include motivational and team-centric messages, indicating a strong emotional connection to the team. The use of hashtags like #HereWeGo and #SteelersNation suggests a desire to foster community and shared excitement.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 21764
- + 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 @boimarv9 reveals an exceptionally influential Twitter presence with 21764 followers. The account demonstrates a content-creator strategy, averaging 4906,6 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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