117,437
Followers
1,721
Following
4,516
Tweets
262.6
Avg Engagement
154
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @bazzabannan25'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:2014-08-15
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,178
- Avg Likes per Tweet:240.7
- Avg Retweets per Tweet:21.9
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,178 tweetsThe account has high engagement with an average of 9,796 likes and 614 retweets per tweet, showing strong interaction with followers.
240.7
Avg Likes/Tweet
21.9
Avg Retweets/Tweet
764,855
Total Likes
69,641
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
33
Median Likes
1
Median Retweets
163
75th Percentile
45,223
Top Tweet
2.24
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
47.5%
Original
39.1%
Replies
10.4%
Retweets
3.0%
Quotes
0.0%
Threads
0.1%
With Media
16.4%
With Links
14.9%
With #Tags
55.9%
With @Mentions
55.1%
With Emojis
74
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.82
Reply/Original Ratio
0.29
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
65.3%
Weekday Posts
34.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,178 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 329 retweets (10% 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 3,178 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 10,000 followersThe audience appears to be football fans, particularly those interested in Premier League and Celtic. The content is casual and relatable, appealing to a broad fan base.
Average
Audience Quality
24.8%
Suspicion Index
35.2%
Low-Quality %
41
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
49.7%
Empty Bio
30.2%
<10 Tweets
12.5%
Mass Following (>2K)
0.0%
New (<90 days)
42.2%
Low Ratio (<0.1)
0.0%
New (<180 days)
93.4%
No URL
20.8%
<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.
9,277,270
Total Potential Reach
41
Median Follower Reach
204
75th Percentile Reach
6.4%
>1K followers
0.8%
>10K followers
0.2%
>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).
48.1%
Creators
4,806 accounts
21.7%
Consumers
2,174 accounts
30.2%
Dormant
3,020 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):
35
Verified Followers
0.35% of total
967
Protected Accounts
9.67% 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 |
|---|---|---|---|
| @chris_kammy | 1,896,383 | Football pundit | Football, TV, Singing |
| @mattletiss7 | 620,723 | Football pundit | Football, pundit, Southampton |
| @IamMzilikazi | 550,141 | Musician | Pan-African music, Album, Rise |
| @talkSPORTDrive | 411,296 | - | - |
| @DFImpressionist | 174,570 | Impressionist | Football, Impressionist, Comedy |
| @Kubwa5Safaris | 160,982 | - | - |
| @Thogden | 160,072 | Football YouTuber | Football, YouTube, Enquiries |
| @FredBoycott | 141,575 | Cricketer | Cricket, Yorkshire, Apanthropist |
| @skysports_sheth | 128,828 | Sports Journalist | Football, Transfers, Podcasts |
| @TomekHajto7 | 127,606 | Footballer | Football, Schalke 04, Derby |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
5,034
Followers With Bio
4,966
Followers Without Bio
50.34%
% With Bio
49.66%
% 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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Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,178 analyzed74,918
Combined Engagement
72,785
Total Likes
2,133
Total Retweets
14,984
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
0%
With @Mentions
40%
With Links
Topical Analysis:
What is jack Grealish actually doing wrong by being in vegas enjoying his time off 🤷♂️ lay off the kids back most other premier league players doing exact same but nothing being said !
Congrats to Celtic champions again brilliant all season 🍀🍀
What a day 😮💨 Mr and Mrs Bannan 😍 https://t.co/8TUF0B6mz4
😮💨😮💨😮💨😮💨😮💨 always Saturday
Family complete welcome Wilf Ryan Bannan 👨👩👧👦😍❤️ https://t.co/bKpREWXb3a
Key Insights & Takeaways
The user often shares opinions on Premier League players and their actions, which indicates a focus on sports commentary. They use humor and casual language to engage with their audience, making their content more approachable. The account frequently mentions specific players and events, suggesting a niche interest in football and its culture.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 117,437
- + 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 @bazzabannan25 reveals an well-established Twitter presence with 117,437 followers. The account demonstrates a content-creator strategy, averaging 262.6 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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