Calvin Bassey
@fulhamfc // @uniqueSG | Insta: cbasseyy || With God All Things Are Possible🙏🏿 ||
67,863
Followers
3
Following
228
Tweets
2,087.4
Avg Engagement
48
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @CalvinBassey'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:2020-06-07
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:213
- Avg Likes per Tweet:1,355.5
- Avg Retweets per Tweet:731.9
- Followers Analyzed:50,000
Engagement Analysis
Based on 213 tweetsHis tweets receive high engagement, averaging 11,089 likes and 446 retweets, indicating a strong connection with his audience.
1,355.5
Avg Likes/Tweet
731.9
Avg Retweets/Tweet
288,719
Total Likes
155,903
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
56
Median Retweets
1,888
75th Percentile
62,624
Top Tweet
30.76
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
18.3%
Original
14.1%
Replies
60.6%
Retweets
7.0%
Quotes
0.0%
Threads
0.0%
With Media
70.9%
With Links
21.6%
With #Tags
81.7%
With @Mentions
77.9%
With Emojis
78
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.77
Reply/Original Ratio
0.12
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
65.3%
Weekday Posts
34.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 213 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 129 retweets (61% 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 213 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 followers are likely football fans and supporters of his clubs, with a focus on those interested in his career progression.
Average
Audience Quality
22.8%
Suspicion Index
32.7%
Low-Quality %
46
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
48.9%
Empty Bio
25.6%
<10 Tweets
9.5%
Mass Following (>2K)
0.0%
New (<90 days)
42.2%
Low Ratio (<0.1)
0.0%
New (<180 days)
94.5%
No URL
16.6%
<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.
21,992,323
Total Potential Reach
46
Median Follower Reach
193
75th Percentile Reach
5.0%
>1K followers
0.3%
>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).
52.5%
Creators
26,271 accounts
21.8%
Consumers
10,918 accounts
25.6%
Dormant
12,811 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):
189
Verified Followers
0.28% of total
8,926
Protected Accounts
13.41% 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 |
|---|---|---|---|
| @AFCAjax | 1,880,992 | Football Club | Football, Soccer, Netherlands |
| @NGSuperEagles | 802,634 | Football Team | Football, Nigeria, Champions |
| @RangersFC | 776,050 | Football Club | Football, Rangers, Sports |
| @footballdaily | 706,916 | Sports Journalist | Breaking news, press conferences, interviews |
| @TheEuropeanLad | 592,208 | Football Enthusiast | Ajax, European football, Messi |
| @Charlie26Adam | 443,946 | Football Coach | Football, Coaching, Management |
| @Moreno | 430,154 | Influencer | Business, Manager, Serious |
| @talkSPORTDrive | 411,538 | - | - |
| @BonganiZungu08 | 288,012 | Footballer | Football, South Africa, Professional |
| @livescore | 287,439 | Sports News | football, scores, updates |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
34,628
Followers With Bio
31,950
Followers Without Bio
52.01%
% With Bio
47.99%
% 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 213 analyzed158,221
Combined Engagement
46,168
Total Likes
112,053
Total Retweets
31,644
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
80%
With @Mentions
80%
With Links
Topical Analysis:
RT @ToniRuediger: Police brutality in Nigeria needs attention. You do that to your own people.💔 It is so sad what is going on there. 🇳🇬 Thi…
RT @GlenKamara4: Enough is enough. https://t.co/uyJLLhIUul
💙 @RangersFC https://t.co/vW0xtSkR0O
For Jimmy 💙💙💙 love you https://t.co/WtRhs8UmPx
RT @IAmJermainDefoe: Let’s bring that trophy home, boss... 🙏🏼🏆 https://t.co/QJ59ayIDlm
Key Insights & Takeaways
He frequently interacts with football clubs and fans, showing his involvement in the community. His content often includes personal gratitude and faith-based messages, highlighting his values. He shares both professional achievements and personal milestones, creating a relatable image.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 67,863
- + 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 @CalvinBassey reveals an exceptionally influential Twitter presence with 67,863 followers. The account demonstrates a content-creator strategy, averaging 2,087.4 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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