Enjin Coin (ENJ) Sentiment & Fear and Greed Index
As of July 7, 2026, Enjin Coin's Ruma Fear & Greed Index is 22 (Fear), its social sentiment score is 56/100 (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
Latest Enjin Coin insights
Enjin Coin (ENJ) experienced a significant 61.5% price surge, fueled by a short squeeze and increased trading volume. This heightened market interest occurs as the project anticipates its upcoming Sensota upgrade, scheduled for Q4. The Sensota upgrade aims to introduce enhancements to Enjin Coin's blockchain features.
Enjin Coin (ENJ) price surged over 70% today, driven by strong market anticipation for the upcoming Sensota Upgrade. This significant price movement was also accompanied by heightened trading volume and short squeeze activity.
Enjin Coin ($ENJ) experienced a significant price surge of approximately 48% in 24 hours, breaking out of a long flat base. This rapid ascent propelled it to the top trending spot on Coingecko. Additionally, $ENJ saw notable outflows from Binance, a technical indicator often interpreted as bullish by market observers.
Frequently asked questions
What is Enjin Coin's Fear & Greed Index?
Enjin Coin's Ruma Fear & Greed Index is currently 22 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 Enjin Coin bullish or bearish right now?
Enjin Coin's social sentiment is currently mixed, with a sentiment score of 56/100 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 Enjin Coin sentiment?
Ruma reads every relevant social post about Enjin Coin 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.