DanielFez
La vida regulinchi | marcas: [email protected]
449,277
Followers
960
Following
12,489
Tweets
1,256.7
Avg Engagement
665
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @DanielFez'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:2010-08-30
- Verification:No
- Location:Oviedo, Asturias.
Data Summary
- Tweets Analyzed:3,244
- Avg Likes per Tweet:968.6
- Avg Retweets per Tweet:288.2
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,244 tweetsHis tweets receive an average of 37,325 likes and 6,080 retweets, indicating strong audience interaction and interest in his content.
968.6
Avg Likes/Tweet
288.2
Avg Retweets/Tweet
3,142,102
Total Likes
934,778
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
7
Median Likes
0
Median Retweets
245
75th Percentile
84,651
Top Tweet
2.8
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
31.5%
Original
54.3%
Replies
5.8%
Retweets
8.4%
Quotes
0.0%
Threads
0.1%
With Media
44.2%
With Links
3.6%
With #Tags
62.3%
With @Mentions
9.1%
With Emojis
55
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.73
Reply/Original Ratio
1.47
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
75.6%
Weekday Posts
24.4%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,244 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 187 retweets (6% 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 3,244 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 followersHis audience is likely interested in language learning, personal development, and relatable content about everyday experiences.
Good
Audience Quality
18.4%
Suspicion Index
27.8%
Low-Quality %
45
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
45.6%
Empty Bio
15.3%
<10 Tweets
5.3%
Mass Following (>2K)
0.0%
New (<90 days)
40.3%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.3%
No URL
10.0%
<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.
59,817,818
Total Potential Reach
45
Median Follower Reach
156
75th Percentile Reach
4.3%
>1K followers
0.5%
>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).
68.3%
Creators
34,166 accounts
16.4%
Consumers
8,206 accounts
15.3%
Dormant
7,628 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):
96
Verified Followers
0.1% of total
9,908
Protected Accounts
9.81% 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 |
|---|---|---|---|
| @AlejandroSanz | 19,797,581 | Singer | Music, Singer, Songwriter |
| @JohnCena | 14,106,764 | Wrestler | Wrestling, Motivation, Self-promotion |
| @DanielSamperO | 3,184,021 | Columnista | Columnista, Youtuber, Comediante |
| @PabloIglesias | 2,711,288 | Politician | politics, journalism, Star Wars |
| @miseliti | 1,386,022 | Actriz-Cantante | Actriz, Canta, Teatro |
| @MoyMu23 | 1,021,184 | Exfutbolista | Music, Sports, Analysis |
| @PlayStationES | 1,005,309 | Gaming | Videojuegos, Exclusivas, Lanzamientos |
| @sirjoancornella | 606,976 | Artist | dark humor, satire, surrealism |
| @pamela_cortesss | 568,788 | Singer-songwriter | Music, Acting, More |
| @pccomponentes | 507,495 | Technology retailer | Tecnología, humor, ofertas |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
56,449
Followers With Bio
44,548
Followers Without Bio
55.89%
% With Bio
44.11%
% 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 3,244 analyzed317,603
Combined Engagement
138,124
Total Likes
179,479
Total Retweets
63,521
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
40%
With @Mentions
100%
With Links
Topical Analysis:
RT @AliExpressES: de nada Andrea, disfruta la lamparita de noche https://t.co/CdWI5AMcjd
RT @yisucrist: acabo d ver a un pájaro explicándole a un erizo k cruce para k no muera. mi dia está completo https://t.co/lkRjHHz4Pe
Como aprender inglés. https://t.co/AwavuBF1Tz
A qué edad te enteraste? https://t.co/O9mgkVZSCI
Y tú ¿lo entendiste? https://t.co/edEI8g1V3v
Key Insights & Takeaways
His content often revolves around language learning and personal anecdotes, which resonate well with his audience. He uses a mix of questions and informative posts to engage followers. His verified status is low, suggesting he may not be a public figure or brand.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 449,277
- + 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 @DanielFez reveals an exceptionally influential Twitter presence with 449,277 followers. The account demonstrates a conversation-first approach, averaging 1,256.7 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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