NEO (NEO) Sentiment & Fear and Greed Index
As of July 5, 2026, NEO's Ruma Fear & Greed Index is 12 (Extreme Fear), its social sentiment score is 0/100 (bearish), it holds 0.00% of crypto social mindshare. These signals are computed by Ruma from social posts across crypto Twitter/X and other sources, scored with large language models rather than keyword counts.
Updated continuously · Source: Ruma
Latest NEO insights
Chainlink has expanded its Cross-Chain Interoperability Protocol (CCIP) and core oracle services to five new blockchain networks. These integrations include Creditcoin, Neo X, Tempo, Ink, and the Robinhood Chain testnet. This strategic move aims to strengthen multi-chain support and enhance broader ecosystem adoption for Chainlink's services.
Neo's co-founder has proposed a significant $461 million treasury overhaul. This initiative aims to fundamentally reform the project's governance model. The proposal specifically seeks to transition away from a 'trust me' governance approach, enhancing transparency and decentralization within the Neo ecosystem.
Neo's co-founder has put forward a proposal for a substantial $461 million overhaul of the project's treasury. This initiative is primarily aimed at reforming Neo's governance model, specifically seeking to end its existing 'trust me' governance structure.
Frequently asked questions
What is NEO's Fear & Greed Index?
NEO's Ruma Fear & Greed Index is currently 12 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 NEO bullish or bearish right now?
NEO'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 Ruma measure NEO sentiment?
Ruma reads every relevant social post about NEO 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.