Crypto Token Social & Narrative Analysis
A structured view of attention, sentiment, influencer signal, community health, and narrative alignment for crypto tokens.
TL;DR
The Social & Narrative Lens turns aggregated social data into a clear, repeatable snapshot of whether a token has real, improving attention or fading, low-quality noise. It scores five pillars (Influencer & KOL, Sentiment, Community, Social Momentum, Social Volume), applies quality penalties for spam and engagement concentration, and pairs the score with narrative interpretation to highlight tailwinds and risks.
How to use it (Web UI)
The Social & Narrative Lens provides a structured workflow: pick a token, generate a report, and read the analysis top-down.
1) Pick a token
Search or paste a contract address and select the chain/network.
2) Run the analysis
Click "Go" to generate a report. The lens pulls aggregated topic snapshots and time-series social metrics and computes the latest signal.
3) Share or revisit
Each run produces a shareable analysis link so you can return later or compare changes over time.
4) Read the report top-down
- Summary: Plain-English view of the current signal, confidence, and bias.
- Social Snapshot: Attention level, share of voice, and recent momentum.
- Sentiment: Current tone and whether it is improving or deteriorating.
- Influencer & KOL Signal: Quality of attention and concentration risk.
- Community Health: Breadth and persistence of participants.
- Narrative Alignment: The market story the token fits into and whether it is heating up or cooling down.
What the Social & Narrative Lens does (high level)
The lens uses aggregated social metrics (not post-level scraping) to assess attention quality and narrative fit, then converts that into a structured report.
1) Data ingestion (topic snapshots + time-series)
We ingest best-effort social metrics from sources like LunarCrush, including:
- Interaction volume and activity counts
- Contributor breadth and post creation
- Share of voice (social dominance)
- Sentiment and spam indicators
2) KPI computation & quality gating
We normalize metrics into a consistent schema, compute short-term and baseline comparisons (7d/30d), and gate the analysis if there is not enough activity. If a token is not "alive" (minimum recent activity), the report returns a low-confidence "no social signal" state.
3) Scoring across five pillars
Each pillar is scored 0-100 using deviation-from-normal logic, then adjusted by a quality factor that penalizes spam and engagement concentration:
4) Narrative alignment (context, not scored)
We interpret where the token fits in current market narratives (AI, RWA, L2, DeFi, Meme, etc.) and whether those narratives are gaining or losing heat. This informs the report but does not directly change the deterministic score.
5) How we summarize it (without black box magic)
The report combines deterministic scoring with a concise narrative that explains what is improving, what is weakening, and what could change the outlook.
Disclaimer
The Social & Narrative Lens uses best-effort data retrieval and automated analysis. Data may be incomplete or delayed, and interpretations can be wrong. This is for educational purposes only and is not financial advice.