Real-Time Sentiment Analysis

• Data Ingestion – Streams live social media posts, developer chats and major news headlines through NLP pipelines. – Prioritizes sources with strong influence on crypto markets, from leading Twitter accounts to on-chain governance forums.

• Sentiment Scoring – Assigns sentiment values (positive, neutral, negative) and intensity scores to each data point using transformer-based language models. – Detects jargon and context (for example “sell the news”) to avoid false positives.

• Event Detection – Watches for sudden spikes in volume of mentions or sentiment shifts around key topics such as regulation, security incidents or protocol upgrades. – Correlates sentiment events with price and volume movements to refine predictive power.

• Signal Filtering – Removes bot noise and pump-and-dump chatter through pattern recognition and source reputation analysis. – Delivers only high-confidence alerts that meaningfully precede market pivots.