Corpse Husband
Faceless. I make music sometimes. I don't even know anymore. also: @CORPSE IG: Corpse_Husband pfp: @vallact No MGMT
3,649,197
Followers
615
Following
1,888
Tweets
27,434.5
Avg Engagement
3,682
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Corpse_Husband'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: Mega Influencer (1M+)
- Account Age:2015-08-08
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:1,849
- Avg Likes per Tweet:26,189.2
- Avg Retweets per Tweet:1,245.3
- Followers Analyzed:50,000
Engagement Analysis
Based on 1,849 tweetsThe account consistently receives high engagement, suggesting a dedicated fanbase that values their content. The mix of likes and retweets indicates a balance between personal connection and broader reach.
26,189.2
Avg Likes/Tweet
1,245.3
Avg Retweets/Tweet
48,423,846
Total Likes
2,302,482
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
1,392
Median Likes
25
Median Retweets
27,074
75th Percentile
635,724
Top Tweet
7.52
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Conversationalist
Highly engaged in discussions
14.8%
Original
82.0%
Replies
1.6%
Retweets
1.7%
Quotes
0.0%
Threads
0.2%
With Media
12.3%
With Links
1.0%
With #Tags
82.8%
With @Mentions
19.5%
With Emojis
61
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
5.55
Reply/Original Ratio
1.07
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
71.2%
Weekday Posts
28.8%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 1,849 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 29 retweets (2% 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 1,849 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 followersThe audience appears to be deeply engaged and empathetic, likely drawn to the authenticity and vulnerability in Corpse_Husband's posts. They are likely fans of music and individuals who share personal health challenges.
Average
Audience Quality
34.2%
Suspicion Index
44.9%
Low-Quality %
3
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
48.3%
Empty Bio
55.5%
<10 Tweets
1.5%
Mass Following (>2K)
0.0%
New (<90 days)
74.4%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.2%
No URL
41.6%
<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.
14,917,129
Total Potential Reach
3
Median Follower Reach
13
75th Percentile Reach
0.9%
>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).
21.6%
Creators
10,797 accounts
22.9%
Consumers
11,440 accounts
55.5%
Dormant
27,763 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):
274
Verified Followers
0.27% of total
11,108
Protected Accounts
11.0% 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 |
|---|---|---|---|
| @SoundCloud | 2,293,416 | Musician | Music, Fair pay, Fan-powered royalties |
| @eaJPark | 2,185,605 | Author | Music, Travel, Food |
| @BishoujoMom | 1,708,920 | Adult entertainer | e-MILF, content creator, favorite |
| @xQc | 1,551,950 | Streamer | Gaming, Streaming, Luminosity |
| @ShapedInternet | 873,669 | Tech Influencer | Technology, Innovation, Internet Culture |
| @frejayeahh | 527,051 | Influencer | Love, Free, Fire |
| @SlimJim | 491,018 | Snack Influencer | meat, long boi, champions |
| @Scoped | 439,320 | Professional Gamer | Gaming, Team Liquid, Professional |
| @luvsickbunni | 409,489 | Content Creator | OF creator, cosplayer, sleepy |
| @ScarleYonaguni | 391,638 | Virtual Streamer | Art, Live, Enchantress |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
52,610
Followers With Bio
48,385
Followers Without Bio
52.09%
% With Bio
47.91%
% 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 1,849 analyzed2,812,052
Combined Engagement
2,621,325
Total Likes
190,727
Total Retweets
562,410
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
40%
With @Mentions
40%
With Links
Topical Analysis:
WE DID IT https://t.co/Sy2XhNlwaA
︎ ︎
@MrBeastYT :)
@Gymshark STREAM E-GIRLS ARE RUINING MY LIFE!
https://t.co/cv8SJzgkZ7
Key Insights & Takeaways
The account's bio and top tweets reveal a focus on personal health struggles and artistic identity. The high engagement suggests a strong emotional connection with followers. The use of verified accounts and cross-platform presence (Instagram, Twitter) indicates a multi-channel strategy.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 3,649,197
- + 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 @Corpse_Husband reveals an exceptionally influential Twitter presence with 3,649,197 followers. The account demonstrates a conversation-first approach, averaging 27,434.5 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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