Keith McPherson
Night time host on @WFAN660🎙Live host on @BleacherReport app ⚾️ blessed Yankee fan 🙏🏿⚡️#BoyDad no Dad Bod 💪🏿 Brooklyn Nets fanalyst 🏀 @talkinnets podcast
33,336
Followers
2,175
Following
122,513
Tweets
96.6
Avg Engagement
276
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Keith_McPherson'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:2013-07-16
- Verification:No
- Location:Jersey Shore ↔️ Jersey City
Data Summary
- Tweets Analyzed:500
- Avg Likes per Tweet:27.6
- Avg Retweets per Tweet:69.0
- Followers Analyzed:31,506
Engagement Analysis
Based on 500 tweetsHis tweets typically receive moderate engagement, with an average of 319 likes and 14 retweets. The content is well-received, as evidenced by the high engagement on his top tweets.
27.6
Avg Likes/Tweet
69.0
Avg Retweets/Tweet
13,810
Total Likes
34,499
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
4
Median Likes
0
Median Retweets
43
75th Percentile
20,144
Top Tweet
2.9
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Conversationalist
Highly engaged in discussions
30.6%
Original
50.6%
Replies
12.8%
Retweets
6.0%
Quotes
0.0%
Threads
0.2%
With Media
28.0%
With Links
8.6%
With #Tags
61.6%
With @Mentions
20.2%
With Emojis
69
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.65
Reply/Original Ratio
0.47
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
64.8%
Weekday Posts
35.2%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 500 tweetsContent Type Distribution
Content Breakdown
What This Reveals About Their Strategy
This account prioritizes community engagement over content broadcasting. With replies making up the majority of their activity, they invest significant time in conversations, building relationships with followers and participating in discussions. This approach typically leads to higher loyalty and more authentic connections.
The 64 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 500 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 31,506 followersHis audience includes sports fans, particularly Yankees and Brooklyn Nets enthusiasts, as well as general entertainment seekers. The content appeals to a mix of casual and dedicated followers.
Good
Audience Quality
18.9%
Suspicion Index
21.4%
Low-Quality %
101
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
35.6%
Empty Bio
12.0%
<10 Tweets
16.8%
Mass Following (>2K)
0.0%
New (<90 days)
38.6%
Low Ratio (<0.1)
0.0%
New (<180 days)
86.0%
No URL
7.2%
<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.
98,873,665
Total Potential Reach
101
Median Follower Reach
333
75th Percentile Reach
10.2%
>1K followers
1.8%
>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).
73.7%
Creators
23,229 accounts
14.3%
Consumers
4,500 accounts
12.0%
Dormant
3,777 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):
824
Verified Followers
2.62% of total
3,473
Protected Accounts
11.02% of total
8 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 |
|---|---|---|---|
| @MTV | 17,691,816 | Entertainment | Music, Entertainment, Awards |
| @JohnCena | 14,105,759 | Wrestler | Wrestling, Motivation, Self-promotion |
| @BeatsByAssassin | 2,266,227 | Multitalented | Actor, Director, Rapper |
| @MLBNetwork | 2,195,347 | Sports Media | Baseball, Social Media, Giveaways |
| @thereallisaann | 1,988,474 | Sports Bettor | Fantasy Sports, Sports Betting, Podcast |
| @KameronBennett | 1,809,535 | DJ | Music, DJing, Booking |
| @KalaniBallFree | 1,245,435 | Athlete | Email Marketing, Entrepreneurship, Social Media |
| @JenSelter | 1,238,941 | Fitness influencer | Fitness, Health, Recipes |
| @TheHoopCentral | 1,140,234 | Sports Analyst | NBA, Analysis, News |
| @Tinashe | 1,109,744 | Musician | Music, Fashion, Beauty |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
20,277
Followers With Bio
11,229
Followers Without Bio
64.36%
% With Bio
35.64%
% 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 500 analyzed27,476
Combined Engagement
0
Total Likes
27,476
Total Retweets
5,495
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
100%
With @Mentions
60%
With Links
Topical Analysis:
RT @KingJames: Welp guess my blue ✔️ will be gone soon cause if you know me I ain’t paying the 5. 🤷🏾♂️
RT @derekjeter: Congratulations @Volpe_Anthony. There’s nothing like playing shortstop for the New York Yankees.
RT @Yankees: Dreamed it. Believed it. Achieved it. https://t.co/F9kMJ2AgNZ
RT @Yankees: Stan' you dig it? https://t.co/mFWx71xM1n
RT @Yankees: Saturday at 161st 👊 #RepBX https://t.co/LfR3HtQ8i3
Key Insights & Takeaways
He leverages his sports affiliations to build a loyal fan base His content is a mix of personal joy, humor, and sports analysis He uses a consistent brand identity with hashtags and emojis to enhance visibility
Strengths
- + Established follower base of 33,336
- + High community engagement through conversations
- + 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 @Keith_McPherson reveals an growing Twitter presence with 33,336 followers. The account demonstrates a conversation-first approach, averaging 96.6 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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