Social Media Sentiment Feeds

Integrate sentiment-based triggers for automated trading strategies, dynamic collateral adjustments, and real-time risk scoring. Build DEXs and lending protocols that react to market mood.

Incorporate community sentiment and hype metrics into NFT floor price oracles and rarity scoring algorithms. Enable data-driven minting, trading, and lending for NFTFi platforms.

Monitor proposal sentiment, delegate reputation, and predict voting outcomes. Equip DAOs with dashboards to gauge community alignment and identify potential governance attacks before they happen.

Leverage social graph and sentiment analysis to build robust reputation scores for airdrop eligibility, creditworthiness, and Sybil attack prevention in token distribution events.

We ingest and normalize data from Twitter/X, Reddit, Discord, and Telegram APIs, applying real-time deduplication and spam filtering to ensure a clean, high-fidelity input stream.

Our proprietary NLP models, fine-tuned on crypto-specific lexicons, classify sentiment (positive/negative/neutral) and extract key topics with >92% accuracy, validated against human-labeled datasets.

We cross-reference social sentiment with real-time on-chain metrics (wallet activity, DEX volumes, gas prices) from providers like The Graph and Chainlink to validate signals and reduce false positives.

Processed sentiment scores are delivered via our audited Chainscore Oracles using a decentralized node network, ensuring tamper-proof data with cryptographic proofs for on-chain verification.

Access normalized sentiment indices and raw data through our low-latency REST API or configure event-driven webhooks for instant alerts when sentiment thresholds are breached.

Our sentiment models are continuously retrained on new data and community feedback, with version-controlled updates deployed seamlessly to maintain accuracy as market dynamics evolve.