Borja Bastón
Jugador del @RealOviedo.
69,018
Followers
223
Following
1,928
Tweets
852.6
Avg Engagement
74
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @BorjaBaston'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:2016-09-22
- Verification:No
- Location:Oviedo, España
Data Summary
- Tweets Analyzed:1,915
- Avg Likes per Tweet:98.6
- Avg Retweets per Tweet:754.0
- Followers Analyzed:10,000
Engagement Analysis
Based on 1,915 tweetsHis tweets receive a significant number of likes and retweets, indicating a loyal and active fan base. The engagement is consistent across his posts, suggesting a strong connection with his followers.
98.6
Avg Likes/Tweet
754.0
Avg Retweets/Tweet
188,843
Total Likes
1,443,862
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
4
Median Likes
12
Median Retweets
247
75th Percentile
89,307
Top Tweet
12.35
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
37.0%
Original
7.6%
Replies
47.3%
Retweets
8.0%
Quotes
0.0%
Threads
0.0%
With Media
88.6%
With Links
62.1%
With #Tags
82.5%
With @Mentions
72.7%
With Emojis
112
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.21
Reply/Original Ratio
0.17
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
72.7%
Weekday Posts
27.3%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 1,915 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 906 retweets (47% 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 1,915 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 followersHis audience is mainly composed of football fans, particularly those supporting Real Oviedo and other local teams. The audience is likely from Spain, given the context of the teams mentioned.
Average
Audience Quality
21.2%
Suspicion Index
26.6%
Low-Quality %
73
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
37.5%
Empty Bio
23.0%
<10 Tweets
12.7%
Mass Following (>2K)
0.0%
New (<90 days)
40.6%
Low Ratio (<0.1)
0.0%
New (<180 days)
92.0%
No URL
15.7%
<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.
40,890,111
Total Potential Reach
73
Median Follower Reach
257
75th Percentile Reach
6.9%
>1K followers
1.0%
>10K followers
0.4%
>50K followers
0.3%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
61.3%
Creators
6,127 accounts
15.7%
Consumers
1,571 accounts
23.0%
Dormant
2,302 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):
28
Verified Followers
0.28% of total
937
Protected Accounts
9.37% 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 | 14,094,198 | Wrestler | Wrestling, Motivation, Self-promotion |
| @LaLiga | 11,882,257 | Sports League | Football, Soccer, International |
| @LaLigaEN | 2,288,009 | Sports Media | Football, La Liga, International |
| @MelendiOficial | 1,694,153 | Singer | Music, Family, Humor |
| @arturoelias | 1,271,950 | Director | technology, philanthropy, sports |
| @sidlowe | 494,178 | Football journalist | Football, politics, history |
| @DanielFez | 439,397 | Influencer | Gaming, Fiction, Twitch |
| @Moreno | 428,721 | Influencer | Business, Manager, Serious |
| @RealOviedo | 334,102 | Football Club | Fútbol, Orgullo, Garra |
| @papigavi | 247,167 | YouTuber | YouTube, meme, Laura |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
6,253
Followers With Bio
3,747
Followers Without Bio
62.53%
% With Bio
37.47%
% 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 1,915 analyzed349,140
Combined Engagement
0
Total Likes
349,140
Total Retweets
69,828
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
100%
With @Mentions
80%
With Links
Topical Analysis:
RT @StephenCurry30: Glory to God! https://t.co/5nlTXUObqp
RT @Bradleysfight: My brave boy has went with the angels today 07/07/17 at 13:35, in mammy and daddies arms surrounded by his... https://t.co/AowNwemgh3
RT @KingJames: WE’RE CHAMPIONS!!!!!!!!! It just now hit me!! #LakerNation💜💛 🏆
RT @LUISENRIQUE21: https://t.co/hI7B10HkW8
RT @paugasol: you'll always be in my heart... my big brother... 💛 https://t.co/ytJ2JDKNaB
Key Insights & Takeaways
His content often includes personal messages and fan interactions, which likely drive engagement. He frequently supports other football teams, which may help broaden his audience and build community ties. The use of emojis and hashtags suggests a focus on emotional connection and brand loyalty.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 69,018
- + 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 @BorjaBaston reveals an well-established Twitter presence with 69,018 followers. The account demonstrates a content-creator strategy, averaging 852.6 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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