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Fear and Greed Index

Sentiment:

KOL Calls

Long/Short Calls

Mindshare:

Intelligence

Emotions

Social Momentum

Feed:

Conviction Index

Followers

Volume ($)

Volatility

Mcap vs BTC

Sentiment Timeframes

Solv Protocol BTC (SOLVBTC) Sentiment & Fear and Greed Index

As of July 20, 2026, Solv Protocol BTC's Nebula Fear & Greed Index is 20 (Extreme Fear), its social sentiment score is 0/100 (bearish), it holds 0.00% of crypto social mindshare. These signals are computed by Nebula from social posts across crypto Twitter/X and other sources, scored with large language models rather than keyword counts.

Updated continuously · Source: Nebula

Fear & Greed20 · Extreme Fear
Sentiment0/100
Mindshare0.00%
Price$64,265 -0.4%

Latest Solv Protocol BTC insights

SOLV Protocol Migrates $700M Tokenized BTC to Chainlink CCIPMay 8, 2026

SOLV Protocol has successfully migrated $700 million in tokenized Bitcoin, specifically SolvBTC and xSolvBTC, to Chainlink's Cross-Chain Interoperability Protocol (CCIP). This significant move integrates a substantial amount of tokenized BTC onto Chainlink's secure cross-chain infrastructure. The migration highlights Chainlink CCIP's growing adoption for facilitating large-scale asset transfers within the decentralized ecosystem.

Frequently asked questions

What is Solv Protocol BTC's Fear & Greed Index?

Solv Protocol BTC's Nebula Fear & Greed Index is currently 20 out of 100, which is Extreme Fear. The index blends social sentiment, social interest, price momentum, volatility, and emotional intensity into a single 0–100 sentiment score, updated continuously.

Is Solv Protocol BTC bullish or bearish right now?

Solv Protocol BTC's social sentiment is currently bearish, with a sentiment score of 0/100 based on how bullish or bearish the crypto social conversation is. Sentiment reflects the mood of the market, not price direction or financial advice.

How does Nebula measure Solv Protocol BTC sentiment?

Nebula reads every relevant social post about Solv Protocol BTC across crypto Twitter/X and other sources and scores it with large language models — capturing bullish/bearish tone, emotion, and who is speaking (from retail to smart money) — rather than counting keywords.