D'Lo Brown
Father,@ChicagoBears fan and supporter of @LFC #YNWA IMPACT!Wrestling Producer. All Interview requests should be directed to rforman@impactwrestling.com
128.028
Followers
922
Following
4.289
Tweets
486,6
Avg Engagement
679
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @dlobrown75'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:2009-08-08
- Verification:No
- Location:Las Vegas, Nevada
Data Summary
- Tweets Analyzed:3.098
- Avg Likes per Tweet:15,2
- Avg Retweets per Tweet:471,3
- Followers Analyzed:50.000
Engagement Analysis
Based on 3.098 tweetsThe user's tweets receive a high level of engagement, with an average of 1,252 likes and 159 retweets, showing a loyal and interactive audience.
15,2
Avg Likes/Tweet
471,3
Avg Retweets/Tweet
47.221
Total Likes
1.460.231
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
2
Median Retweets
19
75th Percentile
331.851
Top Tweet
3,8
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
23,6%
Original
27,3%
Replies
37,2%
Retweets
11,9%
Quotes
0,0%
Threads
0,6%
With Media
43,2%
With Links
35,5%
With #Tags
78,0%
With @Mentions
2,9%
With Emojis
98
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1,16
Reply/Original Ratio
0,32
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
70,6%
Weekday Posts
29,4%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3.098 tweetsContent Type Distribution
Content Breakdown
What This Reveals About Their Strategy
This account prioritizes community engagement over content broadcasting. With replies making up the majority of their activity, they invest significant time in conversations, building relationships with followers and participating in discussions. This approach typically leads to higher loyalty and more authentic connections.
The 1.153 retweets (37% 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 3.098 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 primarily consists of sports and wrestling fans, with a notable interest in Chicago Bears and Liverpool FC, suggesting a passionate and niche following.
Average
Audience Quality
25,6%
Suspicion Index
21,1%
Low-Quality %
62
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
33,5%
Empty Bio
16,0%
<10 Tweets
22,4%
Mass Following (>2K)
0,0%
New (<90 days)
63,0%
Low Ratio (<0.1)
0,0%
New (<180 days)
85,2%
No URL
8,6%
<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.
80.175.331
Total Potential Reach
62
Median Follower Reach
222
75th Percentile Reach
6,4%
>1K followers
0,9%
>10K followers
0,4%
>50K followers
0,2%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
62,4%
Creators
31.194 accounts
21,7%
Consumers
10.828 accounts
16,0%
Dormant
7.978 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):
497
Verified Followers
0.49% of total
9.229
Protected Accounts
9.14% of total
9 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 |
|---|---|---|---|
| @LFC | 23.655.300 | Sports Team | Football, Anti-hate, Unity |
| @JohnCena | 14.101.553 | Wrestler | Wrestling, Motivation, Self-promotion |
| @FoodNetwork | 6.042.312 | Culinary TV | cooking, baking, streaming |
| @IAmJericho | 3.598.256 | Wrestler | Wrestling, Music, Comedy |
| @Variety | 2.912.143 | Entertainment industry | Entertainment, Business, Variety |
| @NatbyNature | 2.468.429 | Wrestler | WWE, wrestling, Nattie |
| @BeatsByAssassin | 2.261.252 | Multitalented | Actor, Director, Rapper |
| @TheMattCardona | 2.187.533 | Wrestler | Pro Wrestling, Podcasting, Events |
| @6BillionPeople | 2.033.131 | - | - |
| @foleyispod | 1.974.765 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
60.986
Followers With Bio
40.010
Followers Without Bio
60.38%
% With Bio
39.62%
% 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 3.098 analyzed791.635
Combined Engagement
0
Total Likes
791.635
Total Retweets
158.327
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
100%
With @Mentions
80%
With Links
Topical Analysis:
RT @BarackObama: John McCain is an American hero & one of the bravest fighters I've ever known. Cancer doesn't know what it's up against. G…
RT @LFC: WE’RE PREMIER LEAGUE CHAMPIONS!! 🏆 https://t.co/qX7Duxoslm
RT @JKCorden: Holy shit. This commercial. https://t.co/aXewAG5C3i
RT @ManCity: https://t.co/Kz89wXt8It
RT @SportsCenter: Like a boss. 😎 https://t.co/zJwlzP7zdj
Key Insights & Takeaways
The user is actively involved in the wrestling industry and has a significant following, indicating a strong personal brand and community engagement. The user's content is highly engaging, with a loyal audience that interacts frequently with their tweets. The user's bio highlights multiple interests and roles, suggesting a multifaceted public persona.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 128.028
- + High community engagement through conversations
- + 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 @dlobrown75 reveals an well-established Twitter presence with 128.028 followers. The account demonstrates a conversation-first approach, averaging 486,6 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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