HAYLEY MCQUEEN
Sports Broadcaster & Event Host
377.004
Followers
1.941
Following
18.056
Tweets
447,8
Avg Engagement
1.350
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @HayleyMcQueen'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:2010-02-12
- Verification:No
- Location:London, England
Data Summary
- Tweets Analyzed:3.243
- Avg Likes per Tweet:97,4
- Avg Retweets per Tweet:350,3
- Followers Analyzed:50.000
Engagement Analysis
Based on 3.243 tweetsHer tweets typically receive around 4,888 likes and 400 retweets on average, indicating a strong and active engagement with her content.
97,4
Avg Likes/Tweet
350,3
Avg Retweets/Tweet
315.920
Total Likes
1.136.160
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
16
Median Likes
1
Median Retweets
81
75th Percentile
199.928
Top Tweet
1,19
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
36,2%
Original
37,2%
Replies
7,1%
Retweets
19,4%
Quotes
0,0%
Threads
0,2%
With Media
42,5%
With Links
17,6%
With #Tags
74,7%
With @Mentions
13,0%
With Emojis
119
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1,03
Reply/Original Ratio
2,72
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
69,2%
Weekday Posts
30,8%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3.243 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 231 retweets (7% 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 3.243 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 followersHer audience includes sports fans, event attendees, and media professionals interested in her coverage and commentary.
Average
Audience Quality
23,6%
Suspicion Index
27,0%
Low-Quality %
69
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
43,7%
Empty Bio
17,1%
<10 Tweets
17,7%
Mass Following (>2K)
0,0%
New (<90 days)
50,3%
Low Ratio (<0.1)
0,0%
New (<180 days)
91,8%
No URL
10,4%
<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.
44.904.217
Total Potential Reach
69
Median Follower Reach
231
75th Percentile Reach
6,8%
>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).
62,8%
Creators
31.387 accounts
20,1%
Consumers
10.064 accounts
17,1%
Dormant
8.549 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):
773
Verified Followers
0.77% of total
13.665
Protected Accounts
13.53% of total
8 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 |
|---|---|---|---|
| @6BillionPeople | 2.035.782 | - | - |
| @UnitedStandMUFC | 1.923.228 | Fan Channel | Manchester United, Global Fanbase, Latest News |
| @David_Ornstein | 1.885.413 | Football Correspondent | - |
| @KameronBennett | 1.812.729 | DJ | Music, DJing, Booking |
| @TheSteinLine | 1.455.190 | Sports Journalist | NBA, correspondent, dad |
| @Sporf | 1.387.214 | Sports Media | Sport, Conversation, Social Chain Group |
| @AliBinAlHussein | 1.090.343 | Entrepreneur | Sports, Travel, Photography |
| @alanshearer | 1.054.330 | Footballer | Football, Analysis, Golf |
| @guardian_sport | 906.315 | Sports News | news, comment, video |
| @ZachBoychuk | 829.558 | Hockey Player | Hockey, Meme/NFT Trading, Ethereum |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
54.674
Followers With Bio
46.324
Followers Without Bio
54.13%
% With Bio
45.87%
% 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 3.243 analyzed734.251
Combined Engagement
0
Total Likes
734.251
Total Retweets
146.850
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
100%
With @Mentions
60%
With Links
Topical Analysis:
RT @IAmJermainDefoe: Sleep tight little one... 💙 https://t.co/iGqLXdvlVi
RT @rickastley: 30 years ago today I said I was Never Gonna Give You Up. I am a man of my word - Rick x https://t.co/VmbMQA6tQB
RT @Autumn_Kamrie: If y’all wanna know how my day is going (And I’m sure you do)... As I’m getting into my car I see these little ass shoes…
RT @LCFC: https://t.co/hQSR0IDWWg
RT @MesutOzil1088: I was so sad that Jerry Quy aka our famous & loyal mascot @Gunnersaurus and integral part of our club was being made red…
Key Insights & Takeaways
She frequently shares breaking news and event highlights, which likely drive her high engagement. Her content often blends personal reflections with professional updates, creating a relatable and authentic presence. She leverages her verified status and media connections to amplify her reach and credibility.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 377.004
- + 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 @HayleyMcQueen reveals an well-established Twitter presence with 377.004 followers. The account demonstrates a conversation-first approach, averaging 447,8 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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