Sergey Akulinin
Продюсер и ведущий «МатчТВ» / «МатчПремьер» ⚽️ Если есть, что предложить, сюда✉️ [email protected] Телеграм тут https://t.me/akulininmatch
59,485
Followers
105
Following
5,333
Tweets
93.5
Avg Engagement
295
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @S_Akulinin'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:2012-03-18
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,183
- Avg Likes per Tweet:23.4
- Avg Retweets per Tweet:70.1
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,183 tweetsAverage likes and retweets indicate a moderate level of interaction. The content is well-received, with a focus on visually appealing and emotionally charged moments from matches.
23.4
Avg Likes/Tweet
70.1
Avg Retweets/Tweet
74,449
Total Likes
223,018
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
6
Median Likes
1
Median Retweets
32
75th Percentile
29,794
Top Tweet
1.57
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
57.0%
Original
19.4%
Replies
13.4%
Retweets
10.1%
Quotes
0.0%
Threads
0.0%
With Media
61.1%
With Links
38.3%
With #Tags
39.0%
With @Mentions
55.1%
With Emojis
116
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.34
Reply/Original Ratio
0.75
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
74.3%
Weekday Posts
25.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,183 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 428 retweets (13% 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 3,183 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 10,000 followersThe audience appears to be football fans and sports enthusiasts interested in match highlights and player moments. They are likely engaged with real-time sports updates and event coverage.
Below Average
Audience Quality
37.5%
Suspicion Index
52.9%
Low-Quality %
2
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
65.0%
Empty Bio
53.6%
<10 Tweets
5.6%
Mass Following (>2K)
0.0%
New (<90 days)
77.6%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.7%
No URL
40.8%
<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.
3,237,044
Total Potential Reach
2
Median Follower Reach
20
75th Percentile Reach
2.2%
>1K followers
0.4%
>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).
26.0%
Creators
2,604 accounts
20.4%
Consumers
2,036 accounts
53.6%
Dormant
5,360 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):
6
Verified Followers
0.06% of total
398
Protected Accounts
3.98% of total
6 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 |
|---|---|---|---|
| @luchogarcia14 | 381,937 | Footballer | Football, Sports, Athlete |
| @Daminous_Purity | 351,398 | Minister | WWE, NFL, FIFA |
| @drissawaked | 265,858 | - | - |
| @Roberto_Moar | 223,077 | Sports Journalist | Sports, Radio, Football |
| @sovsport | 177,339 | Sports Media | Sports, News, Portal |
| @gilliankemmerer | 133,726 | Sports Journalist | KHL, kdrama, archery |
| @gwansunsong | 106,569 | Environmental Activist | Nature, Conservation, Activism |
| @ParssonAlex | 91,197 | Social Media Influencer | Technology, MutualFollows, Reading |
| @NikoLas_112 | 72,683 | - | - |
| @andrey_malgin | 60,929 | Journalist | Politics, Activism, Journalism |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
3,504
Followers With Bio
6,496
Followers Without Bio
35.04%
% With Bio
64.96%
% 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 3,183 analyzed86,025
Combined Engagement
0
Total Likes
86,025
Total Retweets
17,205
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
100%
With @Mentions
60%
With Links
Topical Analysis:
RT @Eidur22Official: Jose still knows how to get the best out of @ChelseaFC #CHEMUN
RT @GaryLineker: Messi is the first player in World Cup history to be a false nine and a false coach in the same game.
RT @SanMarino_FA: The goal is even better with a little bit of Céline Dion. #SMRkaz https://t.co/pTmOgY23Pl
RT @TrollFootball: Pep Guardiola running to tell the Sheikhs to buy Messi after hearing he wants to leave Barcelona. https://t.co/qPEQRHZhX7
RT @brfootball: Football in the last 24 hours 🤯 https://t.co/ySys9se7PV
Key Insights & Takeaways
The account frequently shares visually striking moments from matches, which likely drive engagement. Content often includes emotional and dramatic elements, such as last-minute goals or intense rivalries. There is a focus on major events like the World Cup, suggesting an interest in high-profile sports moments.
Strengths
- + Established follower base of 59,485
- + 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 @S_Akulinin reveals an growing Twitter presence with 59,485 followers. The account demonstrates a content-creator strategy, averaging 93.5 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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