Dan Gheesling
Creating Clean Entertainment Weekdays 9:30AM on https://www.twitch.tv/DanGheesling ♥️ Husband & Dad of 3 🧃Sponsored by @GFuelEnergy 📲 [email protected]
247,754
Followers
592
Following
67,666
Tweets
61.3
Avg Engagement
1,772
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @DanGheesling'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:2009-10-24
- Verification:No
- Location:Dearborn, MI
Data Summary
- Tweets Analyzed:3,250
- Avg Likes per Tweet:59.9
- Avg Retweets per Tweet:1.3
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,250 tweetsDan's tweets typically receive a high number of likes and some retweets, indicating a loyal and interactive audience. His content is well-received and often shared within his community.
59.9
Avg Likes/Tweet
1.3
Avg Retweets/Tweet
194,827
Total Likes
4,347
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
14
Median Likes
0
Median Retweets
53
75th Percentile
7,805
Top Tweet
0.25
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
32.2%
Original
61.1%
Replies
0.1%
Retweets
6.6%
Quotes
0.0%
Threads
0.2%
With Media
27.9%
With Links
3.2%
With #Tags
64.1%
With @Mentions
18.8%
With Emojis
58
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.9
Reply/Original Ratio
72.0
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
79.0%
Weekday Posts
21.0%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,250 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 3 retweets (0% 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 3,250 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 appears to be interested in entertainment, gaming, and personal achievements. They engage with both his original content and sponsored promotions.
Average
Audience Quality
21.9%
Suspicion Index
28.2%
Low-Quality %
24
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
42.1%
Empty Bio
22.3%
<10 Tweets
5.1%
Mass Following (>2K)
0.0%
New (<90 days)
52.2%
Low Ratio (<0.1)
0.0%
New (<180 days)
87.8%
No URL
14.3%
<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.
63,090,173
Total Potential Reach
24
Median Follower Reach
108
75th Percentile Reach
3.5%
>1K followers
0.6%
>10K followers
0.2%
>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).
56.1%
Creators
28,053 accounts
21.6%
Consumers
10,806 accounts
22.3%
Dormant
11,141 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):
387
Verified Followers
0.38% of total
13,327
Protected Accounts
13.2% 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 |
|---|---|---|---|
| @JohnCena | 14,101,229 | Wrestler | Wrestling, Motivation, Self-promotion |
| @Twitch | 9,929,584 | Social Media Manager | Gaming, Community, Support |
| @jamesmaslow | 2,880,952 | Singer | Travel, Music, Fitness |
| @6BillionPeople | 2,034,931 | - | - |
| @GFuelEnergy | 1,668,421 | Energy Drink | Esports, Energy Drink, Gaming |
| @dakotaz | 1,519,489 | Gamer | Gaming, Energy drinks, Streaming |
| @SinghLions | 1,334,430 | Restaurateur | Food, Travel, Influencer |
| @CashNasty | 1,328,785 | YouTuber | Basketball, Gaming, Business |
| @soledadobrien | 1,318,033 | Journalist | working, mom, journalist |
| @elgato | 1,233,727 | Streaming | Stream, Record, Create |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
56,106
Followers With Bio
44,886
Followers Without Bio
55.55%
% With Bio
44.45%
% 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 3,250 analyzed25,272
Combined Engagement
24,236
Total Likes
1,036
Total Retweets
5,054
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
0%
With @Mentions
80%
With Links
Topical Analysis:
🥹🥹🥹 https://t.co/cv1WbpofU6
Didn't watch this season - but congrats to Taylor for winning! Love to see another Michigan winner!
We did it, what a ride... Thanks for being there. ❤️ Signed, It's not going 3000x #ELDENRING https://t.co/f3yCdjPLUu
Good choice https://t.co/TbRRcG28mZ
??? https://t.co/ejf0BfrnYr
Key Insights & Takeaways
His audience is likely interested in entertainment and gaming, as seen through his content and engagement with gaming-related topics. He frequently interacts with his followers, showing a personal and community-focused approach. His use of sponsored content suggests a strategic approach to monetization and brand partnerships.
Strengths
- + Established follower base of 247,754
- + 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 @DanGheesling reveals an growing Twitter presence with 247,754 followers. The account demonstrates a conversation-first approach, averaging 61.3 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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