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Circle USYC (USYC) Sentiment & Fear and Greed Index

As of July 8, 2026, Circle USYC's Ruma Fear & Greed Index is 56 (Neutral), its social sentiment score is 59/100 (mixed), 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

Fear & Greed56 · Neutral
Sentiment59/100
Mindshare0.00%
Price$1.13 -0.2%

Latest Circle USYC insights

BNB Chain RWA TVL Surges to $4B, Doubles Since JanuaryMay 12, 2026

BNB Chain's Real-World Asset (RWA) Total Value Locked (TVL) has rapidly grown to $4 billion. This figure represents a doubling of its TVL since January, marking a significant $2 billion increase. Circle USYC is noted as a key driver of this accelerating growth, indicating increasing institutional adoption within the RWA sector on BNB Chain.

Tether Freezes $70M Linked to North Korean AttacksApr 30, 2026

Arbitrum Security Council member Griff Green highlighted Tether's proactive stance in freezing illicit funds. He specifically noted that Tether has frozen $70 million linked to North Korean cyberattacks. Green contrasted this with Circle's alleged inaction concerning hacker-linked assets.

Frequently asked questions

What is Circle USYC's Fear & Greed Index?

Circle USYC's Ruma Fear & Greed Index is currently 56 out of 100, which is Neutral. The index blends social sentiment, social interest, price momentum, volatility, and emotional intensity into a single 0–100 sentiment score, updated continuously.

Is Circle USYC bullish or bearish right now?

Circle USYC's social sentiment is currently mixed, with a sentiment score of 59/100 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 Circle USYC sentiment?

Ruma reads every relevant social post about Circle USYC 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.