14,124
Followers
620
Following
866
Tweets
290.1
Avg Engagement
31
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @BearAlexander_'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:2013-12-26
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:832
- Avg Likes per Tweet:214.9
- Avg Retweets per Tweet:75.2
- Followers Analyzed:13,340
Engagement Analysis
Based on 832 tweetsThe user has a high average engagement rate with likes and retweets, indicating a dedicated and active audience. Their tweets often receive significant interaction, suggesting they are part of a niche or passionate community.
214.9
Avg Likes/Tweet
75.2
Avg Retweets/Tweet
178,774
Total Likes
62,564
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
2
Median Likes
6
Median Retweets
253
75th Percentile
17,662
Top Tweet
20.54
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
34.6%
Original
16.0%
Replies
41.9%
Retweets
7.5%
Quotes
0.0%
Threads
0.1%
With Media
70.9%
With Links
33.9%
With #Tags
69.8%
With @Mentions
45.7%
With Emojis
106
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.46
Reply/Original Ratio
0.18
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
68.9%
Weekday Posts
31.1%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 832 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 349 retweets (42% 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 832 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 13,340 followersThe audience likely includes sports fans, particularly those interested in college football, and possibly other users in the sports and entertainment space. They may also engage with fans of specific teams and athletes.
Good
Audience Quality
17.9%
Suspicion Index
17.6%
Low-Quality %
151
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
29.6%
Empty Bio
10.0%
<10 Tweets
22.8%
Mass Following (>2K)
0.0%
New (<90 days)
31.9%
Low Ratio (<0.1)
0.0%
New (<180 days)
81.3%
No URL
5.6%
<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.
53,821,381
Total Potential Reach
151
Median Follower Reach
463
75th Percentile Reach
13.5%
>1K followers
3.3%
>10K followers
0.6%
>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).
72.5%
Creators
9,673 accounts
17.5%
Consumers
2,330 accounts
10.0%
Dormant
1,337 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):
207
Verified Followers
1.55% of total
1,167
Protected Accounts
8.75% 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 | 14,106,635 | Wrestler | Wrestling, Motivation, Self-promotion |
| @verified | 4,201,226 | - | - |
| @DezBryant | 3,504,474 | Athlete | Athlete, Founder, #ThrowUpTheX |
| @itsmovies | 1,701,234 | Movie Blogger | Movies, TV shows, Posts |
| @GirlsNoteBook | 1,440,944 | Influencer | Self-improvement, Positive vibes, INFJ |
| @KalaniBallFree | 1,246,323 | Athlete | Email Marketing, Entrepreneurship, Social Media |
| @GeorgiaFootball | 1,107,162 | Football Team | Football, Georgia, Commitment |
| @AdrianPeterson | 1,031,527 | Athlete | Faith, Prayer, AllDay |
| @LeBronJames | 1,006,976 | - | - |
| @solalexasch | 677,713 | Musician | Music, Travel, Tattoos |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
9,387
Followers With Bio
3,953
Followers Without Bio
70.37%
% With Bio
29.63%
% 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 832 analyzed45,091
Combined Engagement
6,929
Total Likes
38,162
Total Retweets
9,018
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
80%
With @Mentions
60%
With Links
Topical Analysis:
RT @espn: "I know what it's like to be unknown and to not have the lights on you and to want to be seen ..." This was incredible from @Dame_Lillard 👏 https://t.co/AXNEZt4A9m
hello world allow me to reintroduce myself 👋🏾 #2023NationalChamps https://t.co/P1lN1KSpyk
RT @GeorgiaFootball: For 𝐆-𝐄-𝐎-𝐑-𝐆-𝐈-𝐀 #GoDawgs #NationalChampionship https://t.co/lKQaxTcEBw
RT @BishopJakes: God's getting ready to take you to the next level!
RT @BishopJakes: God will never leave you!
Key Insights & Takeaways
The user frequently references college football teams and athletes, indicating a strong interest in sports and team culture. They engage with a variety of accounts, including athletes, coaches, and fans, suggesting a community-oriented approach. Their top tweets include celebratory and promotional content, which likely drives engagement and visibility.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 14,124
- + 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 @BearAlexander_ reveals an well-established Twitter presence with 14,124 followers. The account demonstrates a content-creator strategy, averaging 290.1 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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