Financial analysts and trading firms spend significant resources monitoring social media, news, and messaging platforms for market-moving signals. Manual screening is slow and subjective; existing centralized services bottleneck on throughput and may miss relevant signals in niche communities or emerging platforms like Telegram. A decentralized network of independent analysts, economically incentivized to identify and score market-relevant content accurately, can process vastly larger volumes of unstructured data while reducing single-point-of-failure risk.
SN45 addresses this by distributing the analysis workload across a network of miners who classify tweets, Telegram messages, and news articles for sentiment, asset mentions, technical quality, and market impact. Each miner runs local language models to perform real-time analysis; validators then independently grade a sample of results by re-running their own analyzers and award points based on accuracy. Poor performers lose access to work; consistent analysts gain higher dispatch priority.