Kepler (AVIA) Sentiment & Fear and Greed Index
As of August 11, 2026, Kepler's Nebula Fear & Greed Index is 50 (Neutral), its social sentiment score is 37/100 (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
Latest Kepler insights
Rocket Lab reported Q2 2026 earnings on August 10, 2026, with revenue of $234M vs $231M estimate and EPS of $(0.08) in line. The company unveiled GHOST (Global Hypersonic & Orbital Spaceport Technology), a deployable containerized launch system for responsive space missions, and signed a dedicated Neutron launch contract with Kepler Communications for LEO deployment from Wallops Island no earlier than 2028. CEO Peter Beck noted Neutron remains on track for Q4 2026, and the company closed acquisitions of Mynaric and Motiv and announced a deal to acquire Iridium Communications.
Kepler Communications has selected Rocket Lab's Neutron rocket for a dedicated launch as part of its largest network expansion yet. This marks the first time Kepler has booked an entire rocket for constellation deployment rather than flying rideshare, representing a significant commercial milestone for the Neutron program.
Frequently asked questions
What is Kepler's Fear & Greed Index?
Kepler's Nebula Fear & Greed Index is currently 50 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 Kepler bullish or bearish right now?
Kepler's social sentiment is currently bearish, with a sentiment score of 37/100 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 Kepler sentiment?
Nebula reads every relevant social post about Kepler 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.
