Gavin Wood
Founded Polkadot, Kusama, Ethereum, Parity, Web3 Foundation. Building Polkadot. All things Web 3.0
393,072
Followers
156
Following
996
Tweets
644.3
Avg Engagement
4,448
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @gavofyork'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:2009-04-21
- Verification:No
- Location:Zurich, Switzerland
Data Summary
- Tweets Analyzed:599
- Avg Likes per Tweet:341.6
- Avg Retweets per Tweet:302.7
- Followers Analyzed:50,000
Engagement Analysis
Based on 599 tweetsTheir tweets typically receive high engagement, with an average of 7,576 likes and 1,763 retweets. The content often sparks debate and discussion, especially around the future of Web3 and the role of decentralization.
341.6
Avg Likes/Tweet
302.7
Avg Retweets/Tweet
204,641
Total Likes
181,314
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
4
Median Likes
22
Median Retweets
208
75th Percentile
25,439
Top Tweet
1.64
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Curator
Amplifies others content frequently
25.0%
Original
20.4%
Replies
43.1%
Retweets
11.5%
Quotes
0.0%
Threads
0.3%
With Media
48.2%
With Links
14.2%
With #Tags
84.3%
With @Mentions
7.3%
With Emojis
139
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.81
Reply/Original Ratio
0.27
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
82.1%
Weekday Posts
17.9%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 599 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 258 retweets (43% 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 599 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 followersGavofyork's audience primarily consists of developers, investors, and enthusiasts interested in blockchain and decentralized technologies. They engage with a mix of technical and strategic discussions about Web3.0 and crypto.
Average
Audience Quality
21.4%
Suspicion Index
28.4%
Low-Quality %
36
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
40.2%
Empty Bio
26.0%
<10 Tweets
8.8%
Mass Following (>2K)
0.0%
New (<90 days)
40.9%
Low Ratio (<0.1)
0.0%
New (<180 days)
83.5%
No URL
16.6%
<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.
64,651,340
Total Potential Reach
36
Median Follower Reach
135
75th Percentile Reach
5.9%
>1K followers
1.1%
>10K followers
0.3%
>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).
46.2%
Creators
23,082 accounts
27.8%
Consumers
13,907 accounts
26.0%
Dormant
13,011 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):
2,685
Verified Followers
2.66% of total
5,804
Protected Accounts
5.75% of total
4 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 | 14,105,721 | Wrestler | Wrestling, Motivation, Self-promotion |
| @CryptoWeb3_NFT | 4,362,959 | - | - |
| @WhaleCartel | 2,730,563 | - | - |
| @SirKunt | 2,254,773 | - | - |
| @BrianDEvans | 1,141,261 | Entrepreneur | NFTs, Crypto, Digital Marketing |
| @LeBronJames | 1,006,054 | - | - |
| @belufrancese | 1,002,131 | Influencer | NFTs, Crypto, Bitcoin |
| @NEST_Protocol | 930,231 | - | - |
| @lidangzzz | 836,731 | - | - |
| @coinbureau | 792,892 | Crypto Influencer | Cryptocurrency, Trading, Education |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
62,176
Followers With Bio
38,823
Followers Without Bio
61.56%
% With Bio
38.44%
% 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 599 analyzed96,484
Combined Engagement
41,538
Total Likes
54,946
Total Retweets
19,297
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
60%
With @Mentions
0%
With Links
Topical Analysis:
RT @KyivIndependent: ⚡️SBU: Intercepted phone calls shows that Russian troops near Kharkiv were ordered to shoot at civilians, including ch…
Kudos to @facebook for giving us a very real demonstration of why the move to a decentralised Web 3 is necessary and, indeed, inevitable.
RT @NickKnudsenUS: Zelensky drinking coffee and chatting with his fellow Kyiv defenders this morning. Imagine what a moral boost it must b…
I’m sick of hearing crypto confused with a heavily-marketed centralised, mismanaged exchange. FTX’s failure is far from a harbinger of crypto. Quite the opposite: it’s a concrete demonstration of the need for more, better decentralised, trust-free technology.
Events of today in crypto just go to show that genuine decentralisation and well-designed security make a far more valuable proposition than some big tps numbers coming from an exclusive and closed set of servers. If you can't run a full-node yourself then it's just another bank.
Key Insights & Takeaways
Gavofyork emphasizes the necessity of decentralization in the face of centralized failures like FTX. They critique the conflation of crypto with centralized exchanges and advocate for well-designed security. Their tweets often highlight real-world examples to underscore the importance of Web3.0 and decentralized systems.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 393,072
- + 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 @gavofyork reveals an well-established Twitter presence with 393,072 followers. The account demonstrates a content-creator strategy, averaging 644.3 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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