82,433
Followers
396
Following
13,191
Tweets
260.0
Avg Engagement
23
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Riftyish'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:2013-02-19
- Verification:No
- Location:Youtube - Rifty
Data Summary
- Tweets Analyzed:3,201
- Avg Likes per Tweet:252.6
- Avg Retweets per Tweet:7.3
- Followers Analyzed:10,999
Engagement Analysis
Based on 3,201 tweetsRiftyish's tweets typically receive a high number of likes and retweets, indicating a strong and engaged follower base. Their content is well-received and often shared within their community.
252.6
Avg Likes/Tweet
7.3
Avg Retweets/Tweet
808,617
Total Likes
23,497
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
48
Median Likes
0
Median Retweets
364
75th Percentile
9,870
Top Tweet
3.15
Engagement per 1K Followers
Normalized influence metric
Long Tail
Engagement Pattern
Mix of hits and regular posts
Posting Behavior
Content style and format preferences
Conversationalist
Highly engaged in discussions
35.5%
Original
61.6%
Replies
0.2%
Retweets
2.7%
Quotes
0.0%
Threads
0.4%
With Media
28.0%
With Links
0.6%
With #Tags
65.3%
With @Mentions
15.6%
With Emojis
59
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.73
Reply/Original Ratio
10.62
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
73.7%
Weekday Posts
26.3%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,201 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 8 retweets (0% 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 3,201 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 10,999 followersThe audience appears to be interested in content that is humorous, relatable, and offers a behind-the-scenes look at the life of a content creator. They are likely active on social media and enjoy casual, conversational content.
Average
Audience Quality
28.6%
Suspicion Index
26.2%
Low-Quality %
4
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
30.7%
Empty Bio
36.9%
<10 Tweets
2.9%
Mass Following (>2K)
0.0%
New (<90 days)
78.8%
Low Ratio (<0.1)
0.0%
New (<180 days)
88.3%
No URL
21.6%
<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.
19,486,959
Total Potential Reach
4
Median Follower Reach
19
75th Percentile Reach
1.0%
>1K followers
0.2%
>10K followers
0.1%
>50K followers
0.0%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
31.5%
Creators
3,460 accounts
31.6%
Consumers
3,480 accounts
36.9%
Dormant
4,059 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):
21
Verified Followers
0.19% of total
681
Protected Accounts
6.19% of total
2 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 | 14,097,866 | Wrestler | Wrestling, Motivation, Self-promotion |
| @FaZeRug | 2,645,148 | YouTuber | YouTube, Videos, Love |
| @OrdinaryGamers | 763,866 | YouTuber | Gaming, Videos, Gfuel |
| @heyimbee | 587,158 | Content Creator | Gaming, Vlogging, Travel |
| @bbnomula | 369,455 | Rapper | Music, Binesiology, Management |
| @DoniBobes | 77,234 | YouTuber | Minecraft, Gaming, Content Creation |
| @aicandii | 46,275 | - | - |
| @TheMasterOfLuck | 43,285 | Content Creator | Gaming, Streaming, Fatherhood |
| @glitchenergyco | 40,111 | - | - |
| @SuhaibSaqib1 | 39,713 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
7,617
Followers With Bio
3,382
Followers Without Bio
69.25%
% With Bio
30.75%
% 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 3,201 analyzed35,802
Combined Engagement
33,425
Total Likes
2,377
Total Retweets
7,160
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
20%
With @Mentions
100%
With Links
Topical Analysis:
My cat Winston fell asleep mid lick... https://t.co/z5Mw72jFIA
this is literally every single YouTuber/Streamer before they start recording. Yes we all look dead inside while setting it up lmao https://t.co/0wWvbjGsPc
What it feels like to be in a recording with @LachlanYT https://t.co/Oh8qcKXuND
Here is me standing https://t.co/1brQQnYnVn
Just customized my character, I'm excited to play cyberpunk 😊 https://t.co/bpR67g4UNx
Key Insights & Takeaways
Their content often highlights the behind-the-scenes aspects of content creation, which resonates with their audience. They use humor and personal anecdotes to connect with followers, making their tweets feel authentic and relatable. They frequently reference other creators, which suggests a networked approach to content sharing and engagement.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 82,433
- + 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 @Riftyish reveals an well-established Twitter presence with 82,433 followers. The account demonstrates a conversation-first approach, averaging 260.0 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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