Diva Depressão
Olá, Divos e Divas!
673,726
Followers
1,427
Following
73,213
Tweets
950.1
Avg Engagement
302
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @DivaDepressao'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: Macro Influencer (100K+)
- Account Age:2012-08-27
- Verification:No
- Location:São Paulo, Brasil
Data Summary
- Tweets Analyzed:3,161
- Avg Likes per Tweet:429.9
- Avg Retweets per Tweet:520.2
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,161 tweetsThe account has high engagement with an average of 19,531 likes and 1,464 retweets per tweet. Content tends to perform well on trending topics.
429.9
Avg Likes/Tweet
520.2
Avg Retweets/Tweet
1,358,896
Total Likes
1,644,474
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
6
Median Retweets
482
75th Percentile
381,437
Top Tweet
1.41
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
18.0%
Original
12.1%
Replies
53.9%
Retweets
16.0%
Quotes
0.0%
Threads
0.0%
With Media
55.8%
With Links
27.2%
With #Tags
66.9%
With @Mentions
20.8%
With Emojis
91
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.67
Reply/Original Ratio
0.3
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
74.8%
Weekday Posts
25.2%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,161 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 1,705 retweets (54% 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 3,161 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 followersThe audience is primarily Brazilian, interested in entertainment, viral trends, and social media culture. They engage actively with likes and retweets.
Average
Audience Quality
25.9%
Suspicion Index
34.4%
Low-Quality %
9
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
42.6%
Empty Bio
35.4%
<10 Tweets
4.0%
Mass Following (>2K)
0.0%
New (<90 days)
57.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
89.6%
No URL
26.1%
<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.
29,886,282
Total Potential Reach
9
Median Follower Reach
60
75th Percentile Reach
3.5%
>1K followers
0.4%
>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).
44.0%
Creators
22,005 accounts
20.6%
Consumers
10,285 accounts
35.4%
Dormant
17,710 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):
147
Verified Followers
0.15% of total
16,397
Protected Accounts
16.4% of total
3 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 |
|---|---|---|---|
| @FabioPorchat | 9,296,772 | Entertainment | Que História é Essa, Porchat?, Papo de Segunda, Porta dos Fundos |
| @MarceloAdnet | 3,656,430 | Comediante | comediante, ator, roteirista |
| @SinghLions | 1,335,031 | Restaurateur | Food, Travel, Influencer |
| @AndreiaSadi | 1,307,427 | Journalist | Politics, Journalism, News |
| @flaayoficial | 1,227,905 | Singer | Music, Singer, Songwriter |
| @loud_babi | 1,116,202 | - | - |
| @loud_voltan | 1,095,404 | Content Creator | youtuber, influencer, streamer |
| @centralreality | 917,311 | Entertainment News | Reality TV, News, Big Brother |
| @rolealeatorio | 789,931 | Influencer | God, random, blessings |
| @brunnagoncalves | 766,557 | Dancer | Bailarina, Sagitariana, Instagram |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
60,543
Followers With Bio
39,457
Followers Without Bio
60.54%
% With Bio
39.46%
% 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 3,161 analyzed688,473
Combined Engagement
0
Total Likes
688,473
Total Retweets
137,695
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
100%
With @Mentions
60%
With Links
Topical Analysis:
RT @DDonWhytee: When you've been single for too long.😂😂😂😂😂😂 https://t.co/izyLQt4MVD
RT @Scott217: The successful ambush was led by Sgt. Meow. https://t.co/8ZoH7SGJEP
RT @felipeneto: 🚨🚨🚨 ATENÇÃO 🚨🚨🚨 Se você está sendo impedido de votar. Se há alguma ação da PRF ou qlq outra instituição atrasando ou te i…
RT @cat_auras: mood https://t.co/FVwoRqYw9M
RT @felipeneto: É fundamental q esses vídeos se espalhem para q o povo de bem veja a nojeira q é a extrema direita. Nessa cidade de Santa…
Key Insights & Takeaways
The account leverages trending topics and viral moments to drive engagement. Content related to reality TV and social media challenges performs well. The use of hashtags and links to external content helps increase visibility and interaction.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 673,726
- + 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 @DivaDepressao reveals an well-established Twitter presence with 673,726 followers. The account demonstrates a content-creator strategy, averaging 950.1 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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