Sentiment Protocol: A Decentralized Protocol Leveraging Crowd Sourced Wisdom
This addresses the issue of unreliable crowd-sourced opinions for industries like marketing and finance, though it appears incremental by integrating existing concepts.
The paper tackles the problem of incentivizing accurate information in surveys by proposing a decentralized protocol that combines classical polling and prediction markets, resulting in a customizable incentivization framework applicable to event prediction and decentralized autonomous organization governance.
The wisdom of the crowd is a valuable asset in today's society. It is not only important in predicting elections but also plays an essential role in marketing and the financial industry. Having a trustworthy source of opinion can make forecasts more accurate and markets predictable. Until now, a fundamental problem of surveys is the lack of incentives for participants to provide accurate information. Classical solutions like small monetary rewards or the chance of winning a prize are often not very attractive for participants. More attractive solutions, such as prediction markets, face the issue of illegality and are often unavailable. In this work, we present a solution that unites the advantages from classical polling and prediction markets via a customizable incentivization framework. Apart from predicting events, this framework can also be used to govern decentralized autonomous organizations.