Ashley Gavin (seattle 5/14)
stand up every sunday in nyc. we’re having gay sex podcast.
12,387
Followers
483
Following
2,403
Tweets
202.3
Avg Engagement
66
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @AshGavs'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:2009-03-18
- Verification:No
- Location:New York, NY
Data Summary
- Tweets Analyzed:500
- Avg Likes per Tweet:160.7
- Avg Retweets per Tweet:41.7
- Followers Analyzed:11,588
Engagement Analysis
Based on 500 tweetsAshGavs consistently receives high engagement, with an average of 5,809 likes and 594 retweets per tweet, indicating a highly interactive and invested audience.
160.7
Avg Likes/Tweet
41.7
Avg Retweets/Tweet
80,325
Total Likes
20,841
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
6
Median Likes
0
Median Retweets
46
75th Percentile
55,793
Top Tweet
16.33
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
20.4%
Original
67.2%
Replies
9.6%
Retweets
2.8%
Quotes
0.0%
Threads
0.0%
With Media
9.4%
With Links
0.6%
With #Tags
57.6%
With @Mentions
5.8%
With Emojis
76
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
3.29
Reply/Original Ratio
0.29
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
73.8%
Weekday Posts
26.2%
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 48 retweets (10% 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 11,588 followersTheir audience appears to be primarily LGBTQ+ individuals and those interested in comedy and queer culture. The content resonates with people looking for authenticity and raw, unfiltered storytelling.
Good
Audience Quality
13.4%
Suspicion Index
16.3%
Low-Quality %
84
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
23.6%
Empty Bio
13.3%
<10 Tweets
7.2%
Mass Following (>2K)
0.0%
New (<90 days)
28.2%
Low Ratio (<0.1)
0.0%
New (<180 days)
79.3%
No URL
8.9%
<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.
22,550,979
Total Potential Reach
84
Median Follower Reach
289
75th Percentile Reach
8.6%
>1K followers
1.6%
>10K followers
0.5%
>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).
73.3%
Creators
8,499 accounts
13.4%
Consumers
1,550 accounts
13.3%
Dormant
1,539 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):
122
Verified Followers
1.05% of total
2,206
Protected Accounts
19.04% 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 |
|---|---|---|---|
| @JimGaffigan | 3,111,514 | Comedian | Comedy, Touring, Family |
| @sarahcpr | 2,116,825 | Comedian | comedy, author, speaker |
| @druidDUDE | 1,285,461 | Actor | Nature, Magic, Druidry |
| @TayeDiggs | 648,405 | Actor | acting, chocolate, hosting |
| @sarahschauer | 568,616 | Comedian | comedy, LGBTQ+, sarcasm |
| @GirlsWhoCode | 403,112 | Programmer | Tech, Girls, Change |
| @sasha_velour | 364,819 | Drag Queen | Drag, Performance Art, Tour |
| @MacDoesIt | 339,872 | YouTuber | comedy, LGBTQ+, commentary |
| @shanselman | 314,534 | Software Developer | Code, STEM, Podcasts |
| @StephenGlickman | 312,918 | Actor | Big Time Rush, Storks, Party |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
8,849
Followers With Bio
2,739
Followers Without Bio
76.36%
% With Bio
23.64%
% 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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Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 500 analyzed72,259
Combined Engagement
53,833
Total Likes
18,426
Total Retweets
14,452
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
60%
With @Mentions
0%
With Links
Topical Analysis:
ripping the lil panties off a Reese’s is the most erotic thing you can do
RT @thekatesisk: omg the traffic lights are red and green for Christmas 🥺
RT @samuelhmorrison: my gay roommate and i auditioned for the same gay role and we just found out they cast james corden
straight couples: marry your best frie— lesbians: IM FUCKING TRYING
RT @alysiabr0wn: comedians in bars getting covid
Key Insights & Takeaways
The content often challenges traditional relationship norms and highlights queer experiences. Humor is used as a tool to discuss taboo topics like sexuality and jealousy. There is a strong emphasis on personal freedom and self-expression in relationships.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 12,387
- + 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 @AshGavs reveals an well-established Twitter presence with 12,387 followers. The account demonstrates a conversation-first approach, averaging 202.3 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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