Northern 🚆
We're playing a vital role in the north of England by keeping people moving by train. Here to help from 6am to 10pm.
131,134
Followers
281
Following
932,987
Tweets
1.9
Avg Engagement
885
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @northernassist'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:2010-09-24
- Verification:No
- Location:United Kingdom
Data Summary
- Tweets Analyzed:3,250
- Avg Likes per Tweet:1.6
- Avg Retweets per Tweet:0.2
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,250 tweetsThe account has average engagement with around 120 likes and 13 retweets per tweet. The content is mostly informational, with some promotional elements, which may influence engagement levels.
1.6
Avg Likes/Tweet
0.2
Avg Retweets/Tweet
5,358
Total Likes
729
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
0
Median Retweets
0
75th Percentile
325
Top Tweet
0.01
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
5.3%
Original
93.8%
Replies
0.4%
Retweets
0.4%
Quotes
0.0%
Threads
1.7%
With Media
24.3%
With Links
1.0%
With #Tags
94.1%
With @Mentions
9.8%
With Emojis
129
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
17.63
Reply/Original Ratio
0.93
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
78.6%
Weekday Posts
21.4%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,250 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 14 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 3,250 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 likely commuters and residents in the north of England who rely on train services. The content is tailored to those needing travel updates and local event information.
Good
Audience Quality
20.0%
Suspicion Index
27.6%
Low-Quality %
56
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
42.2%
Empty Bio
20.2%
<10 Tweets
10.5%
Mass Following (>2K)
0.0%
New (<90 days)
37.5%
Low Ratio (<0.1)
0.0%
New (<180 days)
85.5%
No URL
13.1%
<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.
40,685,183
Total Potential Reach
56
Median Follower Reach
241
75th Percentile Reach
6.9%
>1K followers
0.6%
>10K followers
0.1%
>50K followers
0.1%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
60.5%
Creators
30,255 accounts
19.2%
Consumers
9,623 accounts
20.2%
Dormant
10,122 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):
221
Verified Followers
0.22% of total
14,084
Protected Accounts
13.95% of total
9 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 | 14,101,630 | Wrestler | Wrestling, Motivation, Self-promotion |
| @BeatsByAssassin | 2,261,267 | Multitalented | Actor, Director, Rapper |
| @TheSteinLine | 1,454,352 | Sports Journalist | NBA, correspondent, dad |
| @SarahBrownUK | 988,282 | Advocate | Education, Global Crisis, Podcast |
| @ericschiffer | 688,360 | CEO | business, media, author |
| @AxelKoster | 598,568 | Recruiter | Global Executive Recruitment, Strategy, Cycling |
| @Reflog_18 | 539,905 | - | - |
| @djkingassassin | 472,093 | DJ | Music, Club, Producer |
| @ZimEye | 420,734 | Journalist | Zimbabwe, Africa, Journalism |
| @b__vllp | 376,159 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
55,467
Followers With Bio
45,528
Followers Without Bio
54.92%
% With Bio
45.08%
% 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 3,250 analyzed884
Combined Engagement
810
Total Likes
74
Total Retweets
177
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
0%
With @Mentions
60%
With Links
Topical Analysis:
test
🚉 Whizzing down the Ormskirk to Preston Line heading for Manchester. 📸 kenmcduff73, Instagram https://t.co/mqKoF5Nw2o
Who's ready for some #SetsEducation? https://t.co/25c8V7lMLM
We are pleased that RMT union have agreed to withdraw strikes. Northern will run standard timetable services, on 30 and 31 March and on 1 and 2 April.
management wondering where and who the test post came from vs. when they see the engagement on the test post https://t.co/dmuwYHB3dQ https://t.co/6PEyJZDUbi
Key Insights & Takeaways
The account uses visual content like photos to enhance engagement. It promotes local events and services, such as #SetsEducation, to connect with the community. The account is active during early mornings and late evenings, suggesting it targets commuters during peak travel times.
Strengths
- + Established follower base of 131,134
- + 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 @northernassist reveals an growing Twitter presence with 131,134 followers. The account demonstrates a conversation-first approach, averaging 1.9 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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