Use Cases Demonstration
Overview
Use Cases for Traders
Use Cases for Researchers
Combined Use Case – Traders & Researchers
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The FourYourSafety (FYS) browser extension enables users to extract intelligence from Twitter/X that would otherwise be hidden, deleted, or lost.
This section expands on the practical use cases, showing how traders, researchers and anyone interested might use FYS.
Challenge: Many token launches are artificially inflated by coordinated influencer hype.
FYS Solution:
Track deleted token promotion tweets.
Monitor when influencers silently remove contract addresses after the hype fades.
Identify early signs of a rug pull by combining follower analysis with tweet deletions.
Outcome: Traders can exit early before liquidity vanishes.
Challenge: Influencer opinions strongly affect short-term token movements.
FYS Solution:
Monitor changes in influencer bios (e.g., new token hashtags).
Detect when they unfollow projects or remove related tweets.
Archive deleted “shill” tweets that often disappear after price crashes.
Outcome: Traders gain a timeline of sentiment shifts to guide entry and exit points.
Challenge: Many insiders create burner accounts to support tokens early.
FYS Solution:
Use “First Followers” analysis to identify who followed new accounts first.
Cross-check if these followers are known insiders or tied to past scams.
Outcome: Traders spot insider clusters, avoiding tokens tied to risky groups.
Challenge: Rug pulls often follow suspicious rebranding or mass follower drops.
FYS Solution:
Profile monitoring detects sudden username or branding shifts.
Follower network analysis highlights abnormal drops or follow-bot purges.
Alerts (Phase 2) notify traders instantly when suspicious patterns appear.
Outcome: Acts as an early-warning radar against exit scams.
Challenge: Traders need risk signals across multiple tokens simultaneously.
FYS Solution:
Aggregate deleted tweets and CA mentions across tracked influencers.
Visualize correlations between multiple projects shilled by the same influencer group.
Tag risky projects in the extension dashboard for easy monitoring.
Outcome: Increases confidence in portfolio allocation decisions.
Challenge: Crypto narratives often vanish when tweets are deleted, making historical research incomplete.
FYS Solution:
Stores deleted tweets for long-term access.
Provides structured datasets for academic, forensic, or journalistic analysis.
Outcome: Researchers preserve primary sources of crypto history.
Challenge: Identifying how influencers interact and amplify each other.
FYS Solution:
Key Followers Analysis maps overlapping follower networks.
First Follower tool highlights which accounts consistently appear early on new projects.
Outcome: Builds a network graph of influence and power structures in crypto Twitter.
Challenge: Crypto trends (e.g., “AI tokens”, “memecoins”) emerge quickly and mutate.
FYS Solution:
Combine tweet timelines, bio changes, and username history.
Document how projects evolve branding or pivot narratives over time.
Outcome: Enables longitudinal studies on meme cycles, hype waves, and market psychology.
Challenge: Scam tactics and influencer behavior repeat in cycles.
FYS Solution:
Analyze how deleted tweets correlate with token price dumps.
Track rebranding attempts across multiple scam accounts.
Detect patterns in how insiders time follows/unfollows.
Outcome: Provides insight into recurring fraud playbooks.
Challenge: Many scams rely on coordinated misinformation campaigns.
FYS Solution:
Archive evidence of influencer deception (deleted shills, fake partnerships).
Provide researchers with forensic data for case studies or regulatory reports.
Outcome: Strengthens transparency and accountability in crypto.
Scenario: A new token appears on Twitter/X. Influencers start promoting it.
Outcome: Both groups gain an informational edge: traders for profit/risk, researchers for documentation/analysis.
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