Alex Greenwood
@mancity / @lionesses / @underarmour
119,897
Followers
534
Following
734
Tweets
596.3
Avg Engagement
338
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @AlexGreenwood'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:2009-08-24
- Verification:No
- Location:Bootle, England
Data Summary
- Tweets Analyzed:710
- Avg Likes per Tweet:505.8
- Avg Retweets per Tweet:90.5
- Followers Analyzed:10,000
Engagement Analysis
Based on 710 tweetsHis tweets receive a high number of likes and retweets, showing strong audience interaction. The use of emojis and hashtags enhances engagement and emotional connection with followers.
505.8
Avg Likes/Tweet
90.5
Avg Retweets/Tweet
359,142
Total Likes
64,237
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
73
Median Likes
11
Median Retweets
535
75th Percentile
16,205
Top Tweet
4.97
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Commentator
Adds perspective to others content
28.5%
Original
14.5%
Replies
23.8%
Retweets
33.2%
Quotes
0.0%
Threads
0.1%
With Media
75.1%
With Links
21.7%
With #Tags
59.7%
With @Mentions
78.3%
With Emojis
88
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.51
Reply/Original Ratio
1.4
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
72.4%
Weekday Posts
27.6%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 710 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 169 retweets (24% 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 710 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 primarily consists of football fans, especially those supporting Manchester City and the Lionesses. They are likely to be passionate, emotionally invested, and interested in team updates and personal insights.
Average
Audience Quality
31.5%
Suspicion Index
40.0%
Low-Quality %
20
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
53.2%
Empty Bio
38.2%
<10 Tweets
11.9%
Mass Following (>2K)
0.0%
New (<90 days)
65.4%
Low Ratio (<0.1)
0.0%
New (<180 days)
93.9%
No URL
26.7%
<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.
22,385,632
Total Potential Reach
20
Median Follower Reach
104
75th Percentile Reach
3.0%
>1K followers
0.3%
>10K followers
0.1%
>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).
36.4%
Creators
3,635 accounts
25.5%
Consumers
2,546 accounts
38.2%
Dormant
3,819 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):
34
Verified Followers
0.34% of total
1,073
Protected Accounts
10.73% of total
3 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 | 14,093,324 | Wrestler | Wrestling, Motivation, Self-promotion |
| @okx | 3,087,149 | Cryptocurrency Exchange | Bitcoin, Crypto, Exchange |
| @SirKunt | 2,290,306 | - | - |
| @Buncaw | 449,287 | - | - |
| @RealRazor | 314,652 | Footballer | Football, Soccer, Sports broadcasting |
| @fratusll | 173,999 | - | - |
| @TheMegaVentures | 65,054 | - | - |
| @greybtc | 40,369 | - | - |
| @TheRealVicAkers | 30,281 | - | - |
| @chrisburrows_03 | 29,633 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
4,678
Followers With Bio
5,322
Followers Without Bio
46.78%
% With Bio
53.22%
% 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 710 analyzed59,364
Combined Engagement
47,089
Total Likes
12,275
Total Retweets
11,873
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
60%
With @Mentions
100%
With Links
Topical Analysis:
ITS COMING HOME 🏆🏴❤️ https://t.co/rN35EnZ9Gd
GOODMORNING 🏆🏴 https://t.co/ZMfp4lGhUu
RT @England: Put your sound on. The #ThreeLions need you to hear this. #MondayMotivation https://t.co/5mlQz2bQPZ
Special summer, With special People and unbelievable fans, still in a dream but loved every minute ✨❤️ 🏴 Time to get back to club mode with @ManCity 💙 https://t.co/o4mlbZjoto
💔Devastated. We gave it everything and we will again. Thankyou everyone for your support. Always proud to be a @lionesses 🦁🏴 https://t.co/FFYVuQtf7g
Key Insights & Takeaways
High engagement suggests a dedicated fanbase that values emotional and celebratory content The use of team and brand affiliations (Manchester City, Lionesses, Under Armour) reinforces brand loyalty and identity The mix of personal and team-related content indicates a balance between personal expression and professional representation
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 119,897
- + 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 @AlexGreenwood reveals an well-established Twitter presence with 119,897 followers. The account demonstrates a content-creator strategy, averaging 596.3 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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