mindshare

Mindshare Analysis Knowledge

Strategic guidance for analyzing market sentiment through mindshare data.

What is Mindshare?

Mindshare measures the share of social attention a project, sector, or user captures relative to the overall conversation. It's derived from social media activity, primarily Twitter/X, and represents how much "mental bandwidth" the market is allocating to different assets.

Key concepts:

• Mindshare Value: Percentage of total attention (e.g., 2.5% means this asset captures 2.5% of all discussion)
• Mindshare Delta: Change in mindshare over the timeframe (positive = gaining attention, negative = losing attention)
• Rank: Position relative to other projects/sectors/users

Decision Framework: When to Use Mindshare

Use mindshare when the signal:

• Mentions social sentiment, narrative, or hype levels
• Claims a project is "trending" or "gaining attention"
• References KOL activity or community buzz
• Discusses narrative rotation (DeFi to AI, L1 to L2, etc.)
• Makes claims about retail interest or social momentum

Skip mindshare when the signal:

• Is purely technical (price patterns, support/resistance)
• Focuses on fundamentals (TVL, revenue, on-chain metrics)
• Discusses tokenomics or unlock schedules
• Is about macro events without social angle

Mindshare confirms sentiment, not price. High mindshare means attention, not necessarily bullish price action. A project can trend for negative reasons.

Signal Types and When to Use Them

Delta Signals (Sudden Spikes)

What: Detects rapid increases in mindshare over a short period.

Use when:

• You want to catch early momentum shifts
• Looking for projects suddenly gaining attention
• Validating claims about "sudden interest" or "breakout buzz"

Interpret:

• High delta (>10%) = significant attention spike
• Moderate delta (3-10%) = notable increase
• Low delta (<3%) = minor uptick

Caveat: Spikes can be driven by FUD, hacks, or drama — not just bullish sentiment.

MA Signals (Sustained Attention)

What: Detects mindshare exceeding its moving average by standard deviations.

Use when:

• Looking for projects with sustained elevated attention
• Validating claims about "continued interest"
• Distinguishing flash-in-the-pan from real momentum

Interpret:

• 2 std dev above MA = significantly elevated

• 1-2 std dev = moderately elevated
• <1 std dev = within normal range

Best for: Confirming that buzz isn't just a one-day spike.

SMA Z-Score Signals (Statistical Anomalies)

What: Uses Z-scores to detect statistically unusual mindshare levels relative to historical norms.

Use when:

• Looking for outliers — projects with attention levels far from their baseline
• Validating "unprecedented interest" claims
• Identifying potential narrative shifts early

Interpret:

• Z-score > 2.0 = highly anomalous (2+ std deviations above mean)
• Z-score 1.0-2.0 = elevated but not extreme
• Z-score < 1.0 = within normal variation

Best for: Catching early-stage momentum before it becomes obvious.

Analysis Workflow

Step 1: Establish Baseline

Before checking signals, understand the current landscape:

• What sectors are trending?
• Who are the top projects by mindshare?
• Is overall attention on majors or altcoins?

Step 2: Match Data to Claim

Select the appropriate tool based on what the signal claims:

Signal Claims	Use This Tool
"X is trending" or "gaining attention"	Project Leaderboard (check rank/delta)
"Sudden spike in interest"	Delta Signals
"Sustained momentum"	MA Signals
"Unprecedented interest"	SMA Z-Score Signals
"KOLs are talking about X"	User Leaderboard by Project
"DeFi rotation happening"	Sector Leaderboard

Step 3: Validate or Contradict

Compare data against the signal's claim:

• Confirms: Data supports the thesis → note in analysis
• Neutral: Data inconclusive → don't weight heavily
• Contradicts: Data opposes the thesis → flag discrepancy

Step 4: Add Context

Mindshare data needs interpretation:

• Is high mindshare from positive or negative attention?
• How does current mindshare compare to historical peaks?
• Who's driving the conversation (KOLs, retail, bots)?

Interpretation Patterns

Confirming Social Momentum

Signal: "SOL is gaining massive attention" Data: SOL #3 on project leaderboard, +15% delta Your take: "Mindshare data confirms elevated attention — SOL ranks #3 with +15% delta over 24h"

Contradicting Hype Claims

Signal: "Everyone is talking about PROJECT_X" Data: PROJECT_X not in top 50, delta +0.5% Your take: "Mindshare data doesn't support broad hype — PROJECT_X not in top 50 and minimal delta"

Detecting Narrative Rotation

Signal: "AI narrative is heating up" Data: AI sector #2 on sector leaderboard, +8% delta; DeFi sector -3% delta Your take: "Sector mindshare confirms AI rotation — AI sector gaining while DeFi declining"

Identifying KOL-Driven Moves

Signal: "Influencers are pushing TOKEN_Y" Data: User leaderboard for TOKEN_Y shows top 5 users account for 60% of mindshare Your take: "Mindshare concentrated among few KOLs — move may lack broad retail interest"

Common Pitfalls

Equating Mindshare with Bullishness

Problem: Assuming high mindshare = bullish. Fix: Mindshare measures attention, not sentiment direction. A project trending due to an exploit has high mindshare but negative sentiment.

Ignoring Baseline

Problem: "2% mindshare is huge!" Fix: For BTC/ETH, 2% is low. For a small-cap, 2% is massive. Compare to historical norms and peer projects.

Chasing Old News

Problem: Acting on a spike that already happened. Fix: Check timestamp on signals. A delta spike from 6 hours ago may already be priced in. Look for fresh signals.

Over-Relying on Single Timeframe

Problem: "24h delta is flat, no momentum." Fix: Check multiple timeframes. 7D might show sustained uptrend even if 24h is consolidating.

Ignoring Who's Talking

Problem: High mindshare but all from low-credibility accounts. Fix: Cross-reference with user leaderboard. Quality of attention matters as much as quantity.

Timeframe Selection Guide

• 30m: Real-time monitoring, catching breaking news
• 24h: Standard daily analysis, most signal contexts
• 3D: Short-term trend, filtering out daily noise
• 7D: Weekly trends, narrative arcs
• 1M: Monthly themes, sector rotations
• 3M: Longer-term trend context
• YTD: Yearly perspective, major narrative shifts

Match timeframe to signal's implied horizon. A "this week's play" signal needs 7D context; a "today's alpha" needs 24h.

Output Format

When presenting mindshare findings in your analysis:

**Mindshare Check:** [Project/Sector] - [Rank] with [delta]%
- [What this means in context]
- [Whether it confirms, contradicts, or is neutral to signal's claim]

Keep it concise. Mindshare is one sentiment input, not the full analysis.

Combining with Other Data

Mindshare works best when combined with:

• Price action: High mindshare + price breakout = momentum confirmation
• Volume: High mindshare + volume spike = real interest
• On-chain: High mindshare + wallet growth = retail accumulation
• TA indicators: High mindshare + RSI oversold = potential bounce catalyst

The strongest signals align across multiple data types.