50,877
Followers
27,593
Following
11,837
Tweets
703.4
Avg Engagement
119
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @aviv_lavi'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: Mid-Tier (10K+)
- Account Age:2019-08-14
- Verification:No
- Location:London
Data Summary
- Tweets Analyzed:3,249
- Avg Likes per Tweet:648.7
- Avg Retweets per Tweet:54.7
- Followers Analyzed:46,545
Engagement Analysis
Based on 3,249 tweetsThe account consistently receives high engagement, indicating a loyal and active audience. The use of humor and relatable topics helps drive likes and retweets.
648.7
Avg Likes/Tweet
54.7
Avg Retweets/Tweet
2,107,521
Total Likes
177,679
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
152
Median Likes
6
Median Retweets
399
75th Percentile
58,907
Top Tweet
13.82
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
62.0%
Original
37.4%
Replies
0.3%
Retweets
0.3%
Quotes
0.0%
Threads
0.7%
With Media
43.0%
With Links
0.4%
With #Tags
37.3%
With @Mentions
40.9%
With Emojis
67
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.6
Reply/Original Ratio
1.1
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
57.0%
Weekday Posts
43.0%
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 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 10 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 3,249 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 46,545 followersThe audience appears to be interested in humor, sports, and pop culture, with a focus on relatable and witty commentary. They likely enjoy content that is both entertaining and shareable.
Good
Audience Quality
17.4%
Suspicion Index
16.9%
Low-Quality %
149
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
24.2%
Empty Bio
17.9%
<10 Tweets
19.8%
Mass Following (>2K)
0.0%
New (<90 days)
26.3%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.9%
No URL
9.5%
<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.
66,565,425
Total Potential Reach
149
Median Follower Reach
544
75th Percentile Reach
15.3%
>1K followers
1.3%
>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).
62.7%
Creators
29,175 accounts
19.4%
Consumers
9,031 accounts
17.9%
Dormant
8,339 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):
50
Verified Followers
0.11% of total
2,665
Protected Accounts
5.73% of total
5 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 | 14,106,811 | Wrestler | Wrestling, Motivation, Self-promotion |
| @verified | 4,201,499 | - | - |
| @gyaigyimii | 1,329,377 | Host | Business, Host, Space |
| @AFTVMedia | 795,398 | Media | Football, Arsenal, Fans |
| @garettnelson | 650,811 | Entrepreneur | Travel, Investing, Adventure |
| @BruceVH | 587,465 | Life Coach | Podcast, Speaker, Optimist |
| @IamMzilikazi | 535,452 | Musician | Pan-African music, Album, Rise |
| @Reflog_18 | 535,346 | - | - |
| @GabbyDarko | 480,992 | Lawyer | Gunner, Pan-Africanist, Legal |
| @wefollowbackd | 457,261 | Football Blogger | Football, News, Sport |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
35,288
Followers With Bio
11,257
Followers Without Bio
75.81%
% With Bio
24.19%
% 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 analyzed183,868
Combined Engagement
166,527
Total Likes
17,341
Total Retweets
36,774
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
0%
With @Mentions
100%
With Links
Topical Analysis:
Typical 🤣 https://t.co/RhHn4pDKuq
Do you realise how iconic this is? https://t.co/Ym6zZYG00U
Imagine wanting to win a trophy and showing up in a Spurs kit? That’s on you mate https://t.co/uHMyNCG08S
LOL RICHARLISON SCORED A TAP IN TO MAKE IT 3-1 (NOT EVEN A WINNER) AND TOOK HIS TOP OFF. ONLY FOR IT TO GET RULED OUT 😂😂😂😂😂😂😂😂😂 https://t.co/8572l4LPtu
This is a different Arsenal… https://t.co/7qS6J2VkrX
Key Insights & Takeaways
The user frequently uses humor and sarcasm to engage their audience. They often reference sports and pop culture in their tweets. Their content is highly shareable and relatable, contributing to high engagement.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 50,877
- + 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 @aviv_lavi reveals an well-established Twitter presence with 50,877 followers. The account demonstrates a content-creator strategy, averaging 703.4 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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