55,945
Followers
140
Following
979
Tweets
1,785.0
Avg Engagement
45
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @rubyodonnellx'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:2013-09-17
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:945
- Avg Likes per Tweet:62.5
- Avg Retweets per Tweet:1,722.5
- Followers Analyzed:10,000
Engagement Analysis
Based on 945 tweetsHer tweets receive a high number of likes and retweets, indicating a loyal and interactive audience. The engagement suggests her content resonates well with her followers.
62.5
Avg Likes/Tweet
1,722.5
Avg Retweets/Tweet
59,094
Total Likes
1,627,750
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
9
Median Likes
5
Median Retweets
93
75th Percentile
405,361
Top Tweet
31.91
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
35.1%
Original
29.8%
Replies
25.4%
Retweets
9.6%
Quotes
0.0%
Threads
0.7%
With Media
46.1%
With Links
17.9%
With #Tags
74.4%
With @Mentions
54.7%
With Emojis
81
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.85
Reply/Original Ratio
0.38
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
72.3%
Weekday Posts
27.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 945 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 240 retweets (25% 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 945 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 followersHer audience appears to be interested in personal stories, social commentary, and celebrity culture. They engage actively with her posts, showing support and interest in her public life.
Below Average
Audience Quality
37.5%
Suspicion Index
100.0%
Low-Quality %
38
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
100.0%
Empty Bio
100.0%
<10 Tweets
0.0%
Mass Following (>2K)
0.0%
New (<90 days)
0.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
92.5%
No URL
100.0%
<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.
7,010,727
Total Potential Reach
38
Median Follower Reach
150
75th Percentile Reach
4.3%
>1K followers
0.7%
>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).
0.0%
Creators
0 accounts
0.0%
Consumers
0 accounts
100.0%
Dormant
10,000 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):
0
Verified Followers
0.0% of total
1,627
Protected Accounts
16.27% 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 |
|---|---|---|---|
| @BarsAndMelody | 752,876 | - | - |
| @StuffWeLikex | 381,871 | Content Creator | Web, KIK, pics |
| @kelvin_fletcher | 270,150 | Actor | Racing, Acting, Strictly |
| @watsoncomedian | 263,522 | Comedian | Novels, Comedy, YouTube |
| @kathyireland | 257,167 | Entrepreneur | Fashion, Design, Empowerment |
| @conquerer1 | 235,251 | Entertainer | MUSIC, AWARDS, CELEBRITIES |
| @HarryGoaz | 232,762 | - | - |
| @mencap_charity | 212,729 | Charity | Support, Learning disability, Carers |
| @E4Tweets | 183,648 | TV Host | Entertainment, Comedy, Reality TV |
| @SamReece | 182,135 | Hairdresser | Hairdressing, Male modeling, Salon ownership |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
5,623
Followers With Bio
4,377
Followers Without Bio
56.23%
% With Bio
43.77%
% 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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Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 945 analyzed1,308,715
Combined Engagement
0
Total Likes
1,308,715
Total Retweets
261,743
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
100%
With @Mentions
80%
With Links
Topical Analysis:
RT @Louis_Tomlinson: Meet my little lad, Freddie 👶 https://t.co/nec7OqwuQR
RT @LeoDiCaprio: Thank you to the Academy and the incredible cast & crew of #TheRevenant. #Oscars
RT @zoewhiite: now THIS is the kind of content I like to see https://t.co/NPtlfLUinM
RT @sian_cosgrove: In other news... the cat over the road is called Walter https://t.co/loIHA2J4mH
RT @blackmirror: You should've seen it coming. https://t.co/E5bYvVJjik
Key Insights & Takeaways
She often shares personal experiences that resonate with her audience, such as her homeless episode and support received. Her tweets reflect a mix of personal reflection and social observation, indicating a balance between private and public life. She uses her platform to comment on public figures and societal issues, which likely contributes to her engagement and follower interaction.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 55,945
- + 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 @rubyodonnellx reveals an exceptionally influential Twitter presence with 55,945 followers. The account demonstrates a content-creator strategy, averaging 1,785.0 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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