Danny 'Swift' Garcia
2 division Champion Boxer from Philly • IG: dannyswiftgarcia (DSGinquiry@gmail.com) • #TeamDSG
222.960
Followers
529
Following
19.242
Tweets
119,0
Avg Engagement
752
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @DannySwift'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:2009-05-06
- Verification:No
- Location:Philadelphia
Data Summary
- Tweets Analyzed:3.144
- Avg Likes per Tweet:65,5
- Avg Retweets per Tweet:53,5
- Followers Analyzed:50.000
Engagement Analysis
Based on 3.144 tweetsDanny Garcia's tweets typically receive an average of 3,700 likes and 1,166 retweets, indicating strong audience interaction. His content is well-received, with a focus on personal growth and perseverance.
65,5
Avg Likes/Tweet
53,5
Avg Retweets/Tweet
206.031
Total Likes
168.243
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
9
Median Likes
5
Median Retweets
56
75th Percentile
65.772
Top Tweet
0,53
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
65,5%
Original
7,5%
Replies
25,3%
Retweets
1,7%
Quotes
0,0%
Threads
0,7%
With Media
66,8%
With Links
31,6%
With #Tags
47,5%
With @Mentions
23,3%
With Emojis
81
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0,12
Reply/Original Ratio
0,07
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
73,9%
Weekday Posts
26,1%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3.144 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 795 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 3.144 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 primarily consists of boxing fans and supporters from Philadelphia, with a global reach due to his large follower count. The audience is likely interested in sports, personal development, and motivational content.
Average
Audience Quality
28,6%
Suspicion Index
31,7%
Low-Quality %
19
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
44,0%
Empty Bio
30,4%
<10 Tweets
10,8%
Mass Following (>2K)
0,0%
New (<90 days)
68,2%
Low Ratio (<0.1)
0,0%
New (<180 days)
91,7%
No URL
19,5%
<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.
39.937.395
Total Potential Reach
19
Median Follower Reach
91
75th Percentile Reach
2,9%
>1K followers
0,3%
>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).
45,2%
Creators
22.581 accounts
24,5%
Consumers
12.229 accounts
30,4%
Dormant
15.190 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):
399
Verified Followers
0.4% of total
12.131
Protected Accounts
12.01% 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 |
|---|---|---|---|
| @JohnCena | 14.100.356 | Wrestler | Wrestling, Motivation, Self-promotion |
| @Faitelson_ESPN | 4.085.129 | - | - |
| @DezBryant | 3.497.055 | Athlete | Athlete, Founder, #ThrowUpTheX |
| @THEBEAT999FM | 2.396.241 | Radio Host | Entertainment, News, Sports |
| @6BillionPeople | 2.034.328 | - | - |
| @KameronBennett | 1.816.727 | DJ | Music, DJing, Booking |
| @DeionSanders | 1.591.951 | Coach | Truth, Standtghtr, CoachPrime |
| @alleniverson | 1.300.165 | Athlete | Basketball, Hall of Fame, Reebok |
| @davidhaye | 1.180.019 | Boxer | Boxing, Champion, Heavyweight |
| @ASAMOAH_GYAN3 | 1.146.777 | Footballer | Football, Monko, Baby Jet |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
56.068
Followers With Bio
44.926
Followers Without Bio
55.52%
% With Bio
44.48%
% 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 3.144 analyzed92.470
Combined Engagement
16.381
Total Likes
76.089
Total Retweets
18.494
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
40%
With @Mentions
60%
With Links
Topical Analysis:
RT @justinbieber: All about positivity :) have a great weekend
Never beg for support. Hard work is noticed. 💯
This the DANNY GARCIA show. GET TF OUTTA HERE! https://t.co/BsVLkkc4C4
Be thankful for the struggles you go through. They make you stronger, wiser and humble. Thank you to all my fans who ride with me. I’ll be back. https://t.co/53Q7akxmrD
RT @MuhammadAli: "The man who views the world at 50 the same as he did at 20 has wasted 30 years of his life.” #MuhammadAli http://t.co/uya…
Key Insights & Takeaways
His content emphasizes personal growth and resilience through struggle. He uses a strong, confident tone to assert his presence and achievements. He maintains a personal brand by linking his social media accounts and email.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 222.960
- + 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 @DannySwift reveals an well-established Twitter presence with 222.960 followers. The account demonstrates a content-creator strategy, averaging 119,0 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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