Disc 🎮
Content Creator/Fortnite Player 900K+ amazing subscribers! Business: [email protected]
188,358
Followers
856
Following
12,339
Tweets
146.7
Avg Engagement
52
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Diiscc'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:2014-06-11
- Verification:No
- Location:New Video ➡️
Data Summary
- Tweets Analyzed:3,249
- Avg Likes per Tweet:101.4
- Avg Retweets per Tweet:45.3
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,249 tweetsDiiscc's tweets receive high engagement, indicating a loyal and interactive fanbase. Their content is well-received, with a mix of humor and relatability driving likes and retweets.
101.4
Avg Likes/Tweet
45.3
Avg Retweets/Tweet
329,476
Total Likes
147,252
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
28
Median Likes
0
Median Retweets
80
75th Percentile
85,283
Top Tweet
0.78
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
16.1%
Original
80.9%
Replies
3.0%
Retweets
0.0%
Quotes
0.0%
Threads
0.1%
With Media
11.9%
With Links
1.9%
With #Tags
78.7%
With @Mentions
24.7%
With Emojis
46
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
5.02
Reply/Original Ratio
0.01
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
69.9%
Weekday Posts
30.1%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,249 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 97 retweets (3% 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 3,249 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 followersDiiscc's audience is primarily interested in gaming, especially Fortnite, and entertainment content. They are likely young, tech-savvy, and active on social media platforms.
Average
Audience Quality
30.3%
Suspicion Index
28.3%
Low-Quality %
3
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
33.3%
Empty Bio
43.3%
<10 Tweets
5.4%
Mass Following (>2K)
0.0%
New (<90 days)
74.3%
Low Ratio (<0.1)
0.0%
New (<180 days)
87.8%
No URL
23.3%
<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.
41,691,375
Total Potential Reach
3
Median Follower Reach
21
75th Percentile Reach
2.8%
>1K followers
0.4%
>10K followers
0.1%
>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).
25.1%
Creators
12,535 accounts
31.6%
Consumers
15,813 accounts
43.3%
Dormant
21,652 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):
343
Verified Followers
0.34% of total
3,100
Protected Accounts
3.07% of total
3 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 | 14,100,269 | Wrestler | Wrestling, Motivation, Self-promotion |
| @garyvee | 3,166,291 | Entrepreneur | Family, CEO, Investor |
| @Clix | 2,169,964 | Professional Gamer | Fortnite, Gaming, Esports |
| @Preston | 1,851,689 | Influencer | Jesus, Business, Handsome |
| @SypherPK | 1,753,992 | Streamer | Gaming, Streaming, Content Creation |
| @gate_io | 1,620,599 | - | - |
| @JeromeASF | 781,129 | Internet Personality | Gaming, Content Creation, Entrepreneurship |
| @Trainwreckstv | 651,906 | Podcaster | Podcasting, Among Us, GFuel |
| @Sheriffayed | 601,459 | Influencer | Instagram, info, sheriffayed |
| @CryptoGemsCom | 522,812 | Sports Analyst | Fenerbahce, FBBasketbol, FENERBAHÇE |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
66,348
Followers With Bio
34,650
Followers Without Bio
65.69%
% With Bio
34.31%
% 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 3,249 analyzed140,075
Combined Engagement
10,433
Total Likes
129,642
Total Retweets
28,015
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
60%
With @Mentions
40%
With Links
Topical Analysis:
RT @pokimanelol: CAR GIVEAWAY 🥰 you could win a brand new TESLA! ✨ retweet + follow ✨ comment #PokiCar #sweepstakes https://t.co/sfnaC4Ag…
RT @scump: THANKS FOR EVERYTHING https://t.co/AiVYCvp9i3
If Jake Paul beats Anderson Silva ill give everyone who likes this tweet $100
damn, fortnite just lost another legend :(
Left @OnePercentHQ on horrible terms.
Key Insights & Takeaways
Diiscc uses bold and attention-grabbing statements to boost engagement. They often reference popular culture and gaming events to connect with their audience. Their content includes both personal experiences and humorous takes on trending topics.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 188,358
- + 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 @Diiscc reveals an well-established Twitter presence with 188,358 followers. The account demonstrates a conversation-first approach, averaging 146.7 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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