Kirsty Hanson
25// @AVWFCOfficial #20 // @TTManagement_
30,470
Followers
645
Following
9,322
Tweets
991.9
Avg Engagement
95
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @KirstyHanson3'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:2012-08-17
- Verification:No
- Location:Yorkshire
Data Summary
- Tweets Analyzed:598
- Avg Likes per Tweet:137.6
- Avg Retweets per Tweet:854.2
- Followers Analyzed:30,043
Engagement Analysis
Based on 598 tweetsHer tweets receive a moderate amount of likes and retweets, indicating a loyal and engaged fan base.
137.6
Avg Likes/Tweet
854.2
Avg Retweets/Tweet
82,310
Total Likes
510,833
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
7
Median Likes
14
Median Retweets
303
75th Percentile
172,313
Top Tweet
32.55
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
8.5%
Original
24.1%
Replies
41.1%
Retweets
26.3%
Quotes
0.0%
Threads
0.2%
With Media
54.8%
With Links
26.1%
With #Tags
76.1%
With @Mentions
73.2%
With Emojis
88
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
2.82
Reply/Original Ratio
0.64
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
62.0%
Weekday Posts
38.0%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 598 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 246 retweets (41% 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 598 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 30,043 followersHer audience appears to be fans of football, particularly those interested in women's football and Manchester United Women's team.
Average
Audience Quality
25.0%
Suspicion Index
22.7%
Low-Quality %
68
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
32.0%
Empty Bio
22.1%
<10 Tweets
21.6%
Mass Following (>2K)
0.0%
New (<90 days)
53.7%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.4%
No URL
13.4%
<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.
90,295,358
Total Potential Reach
68
Median Follower Reach
277
75th Percentile Reach
8.6%
>1K followers
0.8%
>10K followers
0.2%
>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).
56.3%
Creators
16,917 accounts
21.6%
Consumers
6,478 accounts
22.1%
Dormant
6,648 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):
225
Verified Followers
0.75% of total
3,021
Protected Accounts
10.06% of total
6 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 |
|---|---|---|---|
| @ManUtd | 35,590,630 | Sports Team | Football, Manchester, United |
| @JohnCena | 14,105,694 | Wrestler | Wrestling, Motivation, Self-promotion |
| @BBCSport | 10,746,808 | Sports News | Sports, News, Updates |
| @IanWright0 | 2,282,653 | Footballer | Football, Podcasting, Writing |
| @UnitedStandMUFC | 1,913,235 | Fan Channel | Manchester United, Global Fanbase, Latest News |
| @ManUtdMEN | 1,618,410 | Sports Journalist | Football, Manchester United, News |
| @ManUtd_Es | 1,552,074 | Fútbol | Football, Manchester United, Español |
| @EamonnHolmes | 1,103,778 | TV Presenter | TV, Trustee, Television |
| @FlT_MOTIVATION | 438,596 | Fitness Influencer | Fitness, Motivation, Healthy |
| @Moreno | 430,153 | Influencer | Business, Manager, Serious |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
20,440
Followers With Bio
9,603
Followers Without Bio
68.04%
% With Bio
31.96%
% 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 598 analyzed315,799
Combined Engagement
0
Total Likes
315,799
Total Retweets
63,160
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
100%
With @Mentions
40%
With Links
Topical Analysis:
RT @RoyalFamily: It is with deep sorrow that Her Majesty The Queen has announced the death of her beloved husband, His Royal Highness The P…
RT @ManUtd: 𝗕𝗼𝗻𝘀𝗼𝗶𝗿, 𝗥𝗲𝗱𝘀 👋 We have agreed a deal in principle for the transfer of @RaphaelVarane to United! 🔴⚪️⚫️ #MUFC
RT @goal: Christian Eriksen, the whole of football is with you.
RT @ManUtd: A captain. A goalscorer. A legend. And now, 𝗮 𝗺𝗮𝗻𝗮𝗴𝗲𝗿. Happy retirement, @WayneRooney — thank you for the memories ❤️ https:/…
RT @ManUtd: You love to see it 😁 #MUFC @Sanchooo10 https://t.co/QvQ1ibfRGv
Key Insights & Takeaways
She frequently highlights her team's achievements and personal pride in representing them. Her content often includes emotional and motivational messages, resonating with her supporters. She uses hashtags and mentions to connect with her community and promote her team.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 30,470
- + 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 @KirstyHanson3 reveals an well-established Twitter presence with 30,470 followers. The account demonstrates a conversation-first approach, averaging 991.9 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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