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Fear and Greed Index

SENTIMENT:

KOL CALLS

Long/Short Calls

MINDSHARE:

Intelligence

Emotions

Social Momentum

FEED:

Cultiness Index

Followers

Volume ($)

Volatility

Mcap vs BTC

Sentiment Timeframes

Dai (DAI) Sentiment & Fear and Greed Index

As of July 14, 2026, Dai's Nebula Fear & Greed Index is 39 (Fear), its social sentiment score is 24/100 (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 & Greed39 · Fear
Sentiment24/100
Mindshare0.00%
Price$1.0000 +0.0%

Latest Dai insights

Ethereum Co-Founder's Addresses Near Liquidation After $653M ETH PledgeJun 7, 2026

Ethereum co-founder Joseph Lubin's addresses face liquidation risk after depositing 412,430 ETH ($653 million) and borrowing 259 million DAI. The health factor dropped below 1.2 yesterday, signaling potential liquidation if ETH prices decline further.

Coinbase Delists DAI, Converts Remaining Assets to USDSMay 4, 2026

Coinbase is delisting the DAI stablecoin from its platform on May 4th. Following this action, all remaining DAI assets held by users will be automatically converted to USDS. This move directly impacts Coinbase users who currently hold DAI.

Frequently asked questions

What is Dai's Fear & Greed Index?

Dai's Nebula Fear & Greed Index is currently 39 out of 100, which is Fear. The index blends social sentiment, social interest, price momentum, volatility, and emotional intensity into a single 0–100 sentiment score, updated continuously.

Is Dai bullish or bearish right now?

Dai's social sentiment is currently bearish, with a sentiment score of 24/100 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 Dai sentiment?

Nebula reads every relevant social post about Dai 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.