93,789
Followers
604
Following
3,674
Tweets
750.7
Avg Engagement
845
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Keefmorris'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:2010-07-17
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,153
- Avg Likes per Tweet:215.4
- Avg Retweets per Tweet:535.2
- Followers Analyzed:9,998
Engagement Analysis
Based on 3,153 tweetsKeefmorris's tweets consistently receive high engagement, with an average of 34,568 likes and 3,845 retweets per tweet.
215.4
Avg Likes/Tweet
535.2
Avg Retweets/Tweet
679,191
Total Likes
1,687,625
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
2
Median Retweets
24
75th Percentile
705,171
Top Tweet
8.0
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
47.0%
Original
29.2%
Replies
21.9%
Retweets
1.8%
Quotes
0.0%
Threads
0.2%
With Media
16.1%
With Links
27.7%
With #Tags
67.1%
With @Mentions
4.9%
With Emojis
64
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.62
Reply/Original Ratio
0.08
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
72.9%
Weekday Posts
27.1%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,153 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 691 retweets (22% 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 3,153 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 9,998 followersThe audience appears to be interested in motivational and spiritual content, with a focus on community and loyalty.
Average
Audience Quality
23.6%
Suspicion Index
25.2%
Low-Quality %
47
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
36.8%
Empty Bio
20.8%
<10 Tweets
13.1%
Mass Following (>2K)
0.0%
New (<90 days)
56.4%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.0%
No URL
13.5%
<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.
34,727,774
Total Potential Reach
47
Median Follower Reach
197
75th Percentile Reach
5.3%
>1K followers
0.8%
>10K followers
0.3%
>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).
61.6%
Creators
6,159 accounts
17.6%
Consumers
1,761 accounts
20.8%
Dormant
2,078 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):
105
Verified Followers
1.05% of total
1,056
Protected Accounts
10.56% 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 | 14,093,303 | Wrestler | Wrestling, Motivation, Self-promotion |
| @mcuban | 8,835,961 | Entrepreneur | NFTs, Entrepreneurship, Investing |
| @dallasmavs | 2,239,480 | Sports Team | Basketball, Mavericks, MFFL |
| @BrooklynNets | 2,030,406 | Sports Team | Basketball, Nets Level, Brooklyn |
| @BabyDogeCoin | 1,926,991 | - | - |
| @HoHighlights | 292,307 | Sports Media | Sports, Youth Culture, Highlights |
| @darcydonavan | 240,748 | Actress | Acting, Music, Producing |
| @tiagosplitter | 202,289 | Basketball Coach | Basketball, Coaching, Cigars |
| @rebeccagrants | 188,797 | Sportscaster | movies, TV, sports |
| @AmyTaylorNYC | 122,486 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
6,316
Followers With Bio
3,684
Followers Without Bio
63.16%
% With Bio
36.84%
% 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 3,153 analyzed1,227,862
Combined Engagement
143,434
Total Likes
1,084,428
Total Retweets
245,572
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
60%
With @Mentions
40%
With Links
Topical Analysis:
RT @POTUS: Thank you for everything. My last ask is the same as my first. I'm asking you to believe—not in my ability to create change, but in yours.
RT @ChiefBPartridge: I ask EVERYONE who sees this tweet to please re-tweet it. Help bring her home to her family safe. https://t.co/dOyi32McfO
RT @Jared_Sully0: Rest In Peace Kobe Bryant Rest In Peace Gianna Bryant Rest In Peace Alyssa Altobelli Rest In Peace John Altobelli Rest In Peace Kerry Altobelli Rest in Peace Christina Mauser Rest in Peace Sarah Chester Rest in Peace Payton Chester Rest in Peace Ara Zobayan
Run it back! #Lakeshow
All Glory to God!! https://t.co/SdE9A2Ml2E
Key Insights & Takeaways
Keefmorris uses hashtags effectively to amplify reach and community interaction. Their content often includes motivational and spiritual themes, resonating with a dedicated fanbase. They frequently reference events and community support, indicating a strong connection with their followers.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 93,789
- + 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 @Keefmorris reveals an well-established Twitter presence with 93,789 followers. The account demonstrates a content-creator strategy, averaging 750.7 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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