abbeychan
Newbie
- Sep 3, 2023
- 41
- 9
I’ve been working on a TikTok account analytics model recently and decided to stress test it on one of the most high-traffic profiles — Donald Trump’s new TikTok account.
I am not sharing any links here to avoid rule violations; only showing the charts and scoring outputs generated by my model.
Key points of the analysis:
1. Follower Authenticity Score (FAS)
My scoring system evaluates patterns like abnormal following ratios, suspicious engagement behavior, and audience distribution anomalies. Trump’s account shows a mix of real users and typical viral-profile artifacts (charts attached).
2. Engagement Structure
I analyzed the like/comment ratio, follower growth curve, and interaction density. The engagement is extremely top-heavy but still aligns with high-visibility political profiles.
3. Audience Profile Snapshot
The model extracts rough audience behavior clusters — active watchers, passive followers, hype-cycle followers, and low-signal accounts.
4. Risk Indicators
Includes flags for unusual spikes, recycled follower blocks, and interaction inconsistencies. Some indicators triggered, but overall within expectations for a political/public-figure account.
All screenshots and scoring outputs are attached below.
Not promoting anything — just sharing the data results in case anyone here is curious about how TikTok’s political follower bases look under a scoring model.
If anyone wants me to run this kind of analysis on other public accounts, let me know. I’m using my own scoring logic and can generate similar breakdowns.
I am not sharing any links here to avoid rule violations; only showing the charts and scoring outputs generated by my model.
Key points of the analysis:
1. Follower Authenticity Score (FAS)
My scoring system evaluates patterns like abnormal following ratios, suspicious engagement behavior, and audience distribution anomalies. Trump’s account shows a mix of real users and typical viral-profile artifacts (charts attached).
2. Engagement Structure
I analyzed the like/comment ratio, follower growth curve, and interaction density. The engagement is extremely top-heavy but still aligns with high-visibility political profiles.
3. Audience Profile Snapshot
The model extracts rough audience behavior clusters — active watchers, passive followers, hype-cycle followers, and low-signal accounts.
4. Risk Indicators
Includes flags for unusual spikes, recycled follower blocks, and interaction inconsistencies. Some indicators triggered, but overall within expectations for a political/public-figure account.
All screenshots and scoring outputs are attached below.
Not promoting anything — just sharing the data results in case anyone here is curious about how TikTok’s political follower bases look under a scoring model.
If anyone wants me to run this kind of analysis on other public accounts, let me know. I’m using my own scoring logic and can generate similar breakdowns.