Adrian Peterson
“Faith of a mustard seed” Therefore I tell you, whatever you ask for in prayer, believe that you have received it, and it will be yours. #AllDay
1,003,762
Followers
682
Following
3,556
Tweets
841.8
Avg Engagement
3,956
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @AdrianPeterson'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: Mega Influencer (1M+)
- Account Age:2009-03-19
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,077
- Avg Likes per Tweet:549.7
- Avg Retweets per Tweet:292.1
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,077 tweetsHis tweets receive a high number of likes and retweets on average, indicating strong audience interaction. The content is both personal and engaging, driving consistent engagement.
549.7
Avg Likes/Tweet
292.1
Avg Retweets/Tweet
1,691,477
Total Likes
898,774
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
27
Median Likes
17
Median Retweets
446
75th Percentile
95,905
Top Tweet
0.84
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
49.2%
Original
9.3%
Replies
30.1%
Retweets
11.4%
Quotes
0.0%
Threads
0.5%
With Media
51.1%
With Links
28.9%
With #Tags
54.6%
With @Mentions
22.4%
With Emojis
103
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.19
Reply/Original Ratio
0.38
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
72.4%
Weekday Posts
27.6%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,077 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 926 retweets (30% 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 3,077 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 followersHis followers are likely fans of his football career and interested in his personal life. The audience seems to appreciate his faith-based content and candid moments.
Good
Audience Quality
19.3%
Suspicion Index
22.3%
Low-Quality %
69
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
36.3%
Empty Bio
13.7%
<10 Tweets
12.7%
Mass Following (>2K)
0.0%
New (<90 days)
43.8%
Low Ratio (<0.1)
0.0%
New (<180 days)
87.6%
No URL
8.2%
<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.
87,461,549
Total Potential Reach
69
Median Follower Reach
250
75th Percentile Reach
6.2%
>1K followers
0.8%
>10K followers
0.3%
>50K followers
0.2%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
68.7%
Creators
34,348 accounts
17.6%
Consumers
8,812 accounts
13.7%
Dormant
6,840 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):
1,025
Verified Followers
1.01% of total
10,075
Protected Accounts
9.98% 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 | 14,105,354 | Wrestler | Wrestling, Motivation, Self-promotion |
| @Wale | 6,228,799 | Writer | anti-hero, super genius, music |
| @PatMcAfeeShow | 2,834,929 | Sports commentator | Sports, Betting, Entertainment |
| @Seahawks | 2,574,445 | Sports Team | Football, Seattle, #GoHawks |
| @RickWarren | 2,258,323 | Pastor | Faith, Purpose, Church |
| @LarryFitzgerald | 2,158,088 | Football Player | traveler, philanthropist, photographer |
| @SInow | 1,858,907 | Sports Media | Sports, TikTok, Instagram |
| @KameronBennett | 1,810,601 | DJ | Music, DJing, Booking |
| @pizzahut | 1,696,057 | Restaurant | Pizza, Literacy, Gaming |
| @MLBONFOX | 1,547,902 | Sports Media | Baseball, FOX Sports, MLB |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
52,245
Followers With Bio
48,749
Followers Without Bio
51.73%
% With Bio
48.27%
% 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 3,077 analyzed390,594
Combined Engagement
272,845
Total Likes
117,749
Total Retweets
78,119
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
0%
With @Mentions
60%
With Links
Topical Analysis:
#NewProfilePic https://t.co/DHYfyKCbHo
I could no longer withhold this from you all! My secret is out... I am Donatello https://t.co/XbwpSTiGrP
I think I can still do that 🤣😂🦾 https://t.co/p8RPsuJz8N
God Bless everyone and thank u so much.
So my daughter is laying here under me and just out the blue she says... I can't believe you lost to the Browns Daddy! Smh
Key Insights & Takeaways
Peterson uses his platform to share personal and faith-based messages, which resonate with his audience. His content includes a mix of humor and sincerity, appealing to a broad range of followers. He frequently shares updates about his personal life, which increases audience connection and engagement.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 1,003,762
- + 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 @AdrianPeterson reveals an well-established Twitter presence with 1,003,762 followers. The account demonstrates a content-creator strategy, averaging 841.8 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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