853,280
Followers
868
Following
8,254
Tweets
4,181.2
Avg Engagement
1,083
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @VanessaMorgan'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:2009-04-06
- Verification:No
- Location:Los Angeles
Data Summary
- Tweets Analyzed:3,084
- Avg Likes per Tweet:2,315.6
- Avg Retweets per Tweet:1,865.6
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,084 tweetsVanessa Morgan's tweets receive an average of 77k likes and 10k retweets, indicating high audience engagement. Her content is well-received and often shared across her followers' networks.
2,315.6
Avg Likes/Tweet
1,865.6
Avg Retweets/Tweet
7,141,279
Total Likes
5,753,462
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
68
Median Likes
31
Median Retweets
2,218
75th Percentile
624,229
Top Tweet
4.9
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
54.9%
Original
12.9%
Replies
23.1%
Retweets
9.1%
Quotes
0.0%
Threads
0.8%
With Media
67.0%
With Links
24.8%
With #Tags
49.2%
With @Mentions
55.3%
With Emojis
76
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.24
Reply/Original Ratio
0.39
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
76.6%
Weekday Posts
23.4%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,084 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 712 retweets (23% 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 3,084 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 primarily consists of fans of Riverdale and entertainment enthusiasts who engage with her personal and show-related content. The audience is highly interactive, showing strong support through likes and retweets.
Below Average
Audience Quality
35.8%
Suspicion Index
45.3%
Low-Quality %
2
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
43.3%
Empty Bio
59.7%
<10 Tweets
3.8%
Mass Following (>2K)
0.0%
New (<90 days)
77.5%
Low Ratio (<0.1)
0.0%
New (<180 days)
94.8%
No URL
47.3%
<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.
23,881,634
Total Potential Reach
2
Median Follower Reach
13
75th Percentile Reach
1.3%
>1K followers
0.1%
>10K followers
0.0%
>50K followers
0.0%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
22.1%
Creators
11,030 accounts
18.2%
Consumers
9,107 accounts
59.7%
Dormant
29,863 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):
80
Verified Followers
0.08% of total
11,095
Protected Accounts
10.99% of total
2 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 | 14,105,419 | Wrestler | Wrestling, Motivation, Self-promotion |
| @TeenVogue | 3,278,231 | Fashion Editor | Fashion, Beauty, Empowerment |
| @madisonpettis | 1,402,990 | Actress | Movies, American Pie, Netflix |
| @MilesSTEREOS | 861,763 | Musician | Guitarist, Writer, Producer |
| @NOH8Campaign | 801,955 | Activism | equality, bullying, discrimination |
| @THE_THEO_FORD | 469,456 | - | - |
| @iamprincekash | 409,981 | - | - |
| @justjaredjr | 356,539 | Entertainment Blogger | celebrities, teens, entertainment |
| @RichardSHarmon | 312,887 | - | - |
| @johnhfio | 240,418 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
58,771
Followers With Bio
42,228
Followers Without Bio
58.19%
% With Bio
41.81%
% 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 3,084 analyzed1,593,448
Combined Engagement
0
Total Likes
1,593,448
Total Retweets
318,690
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
100%
With @Mentions
40%
With Links
Topical Analysis:
RT @omgAdamSaleh: We got kicked out of a @Delta airplane because I spoke Arabic to my mom on the phone and with my friend slim... WTFFFFFFF…
RT @Kaepernick7: Believe in something, even if it means sacrificing everything. #JustDoIt https://t.co/SRWkMIDdaO
RT @NatGeoChannel: A fight breaks out when a husband comes home and finds his wife with another penguin. https://t.co/9ejYGcJ5TJ
RT @DaRealAmberRose: Awww @kanyewest are u mad I'm not around to play in ur asshole anymore? #FingersInTheBootyAssBitch☝
RT @JordanPeele: We got you, John.
Key Insights & Takeaways
Her top tweets include emotional posts and show-related updates, which likely drive high engagement. She frequently shares personal and emotional content, which resonates with her audience. Her verified status is low, suggesting she may not be a public figure or brand, but still maintains a loyal fan base.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 853,280
- + 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 @VanessaMorgan reveals an exceptionally influential Twitter presence with 853,280 followers. The account demonstrates a content-creator strategy, averaging 4,181.2 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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