MongoDB
A developer data platform for developers to do their best work. #LoveYourDevelopers
452,959
Followers
6,477
Following
23,549
Tweets
15.0
Avg Engagement
5,669
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @MongoDB'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:2008-12-12
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,245
- Avg Likes per Tweet:12.2
- Avg Retweets per Tweet:2.9
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,245 tweetsPosts receive consistent likes and retweets, indicating a loyal and active community. The engagement is moderate, suggesting a focused but not highly viral audience.
12.2
Avg Likes/Tweet
2.9
Avg Retweets/Tweet
39,488
Total Likes
9,270
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
2
Median Likes
0
Median Retweets
16
75th Percentile
3,244
Top Tweet
0.03
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
41.7%
Original
49.7%
Replies
7.9%
Retweets
0.7%
Quotes
0.0%
Threads
0.0%
With Media
66.3%
With Links
15.2%
With #Tags
76.2%
With @Mentions
40.4%
With Emojis
162
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.19
Reply/Original Ratio
0.09
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
94.4%
Weekday Posts
5.6%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,245 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 256 retweets (8% 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 3,245 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 primary audience is developers and tech professionals interested in data platforms and programming. The content appeals to both beginners and experienced developers.
Average
Audience Quality
34.9%
Suspicion Index
47.0%
Low-Quality %
5
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
51.8%
Empty Bio
55.7%
<10 Tweets
3.8%
Mass Following (>2K)
0.0%
New (<90 days)
72.2%
Low Ratio (<0.1)
0.0%
New (<180 days)
84.4%
No URL
42.2%
<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.
22,240,659
Total Potential Reach
5
Median Follower Reach
26
75th Percentile Reach
1.6%
>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).
22.4%
Creators
11,192 accounts
21.9%
Consumers
10,970 accounts
55.7%
Dormant
27,838 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):
573
Verified Followers
0.57% of total
8,693
Protected Accounts
8.69% of total
4 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 | 14,104,295 | Wrestler | Wrestling, Motivation, Self-promotion |
| @depthsofwiki | 772,216 | Wikipedia Enthusiast | Wikipedia, favorite things, fluffybabycow |
| @philosophytweet | 386,806 | - | - |
| @JacquelineRLine | 367,132 | Influencer | Fashion, Beauty, Lifestyle |
| @ryanfoland | 324,467 | Speaker | sailing, speaking, startups |
| @WomenWhoCode | 320,610 | Tech Nonprofit | technology, women empowerment, career development |
| @Asamsakti | 286,703 | Art Lover | Art, Technology, Tea |
| @ExcelHumor | 276,397 | Comedy | Excel, Humor, Memes |
| @DThompsonDev | 257,671 | Software Developer | Software dev, DevEcosystems, Public Speaking |
| @StackOverflow | 234,180 | Tech Support | technology, developers, coding |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
55,578
Followers With Bio
44,422
Followers Without Bio
55.58%
% With Bio
44.42%
% 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 3,245 analyzed7,692
Combined Engagement
7,123
Total Likes
569
Total Retweets
1,538
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
0%
With @Mentions
0%
With Links
Topical Analysis:
Write a developer horror story in 5 words or less. 🎃
What's best programming language to learn for new developers?🤔 And why?
If you weren't a developer, what would you be? 💼
“We’ve always used a relational database.” 🚩🚩🚩🚩🚩🚩🚩🚩🚩
When did you first know your career would be in tech? 💻
Key Insights & Takeaways
The account uses creative and thought-provoking prompts to spark discussion and engagement. It balances technical questions with lighter, more relatable content to maintain audience interest. The use of emojis and hashtags helps to make the content more approachable and shareable.
Strengths
- + Established follower base of 452,959
- + 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 @MongoDB reveals an growing Twitter presence with 452,959 followers. The account demonstrates a conversation-first approach, averaging 15.0 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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