In the Web2 era, "sentiment_analysis" was a centralized process where corporations used proprietary AI models to analyze user-generated text for private business intelligence. This analysis of social media posts, product reviews, and news articles was performed in a black box to gauge brand reputation or predict market trends. The resulting sentiment score was a private data asset, and the individuals whose opinions were being analyzed had no visibility into or control over how their data was interpreted and used. In the Web3 and Fourth Industrial Revolution (4IR) paradigm, "sentiment_analysis" becomes a transparent, on-chain signal that can be used as a public utility to trigger automated actions. The analysis is applied not just to text but to auditable on-chain activities, like buy/sell pressure in a DeFi market or voting patterns in a DAO. The resulting sentiment score can be published on-chain by a decentralized network, creating a verifiable data feed that a smart contract can use to automatically execute a trade, adjust a protocol parameter, or even influence a decentralized governance outcome, turning sentiment from a private insight into a public, executable trigger.