Big Data Protocol

Big Data Protocol partnered with Skim Ai to process social media data around crypto assets, NFTs, and more, across Twitter, Telegram, and Discord for a better understanding of market sentiment.

Industry: Crypto & Blockchain

Who are Big Data Protocol?

Big Data Protocol is a decentralized data exchange protocol that leverages blockchain technology to enable secure and transparent buying, selling, and sharing of data. The platform offers access to a diverse range of data sets from various sources while ensuring user privacy and security.

The mission? To democratize access to data and create a fairer data economy, benefiting all stakeholders.

The challenge

Adapting sentiment analysis tools to analyze the vast amounts of data generated by the cryptocurrency industry. Specifically, the platform needed to develop a solution that could effectively analyze social media data from sources such as Twitter, Telegram, and Discord while accommodating the use of new industry-specific terms and jargon.

The Goal

Big Data Protocol’s goal was to leverage Generative AI to develop a customized sentiment analysis tool that could accurately capture and interpret the nuances of crypto-related conversations across various social media platforms. They wanted to create data sets that add value to traders, researchers, and investors seeking to understand the cryptocurrency market.

The customized sentiment analysis tool enabled Big Data Protocol to summarize data and extract insights on market sentiment, interactions, and trends, helping users gain a better understanding of which currencies are on the rise or fall.

The solution

The Skim Ai team built an AI-powered sentiment analysis tool leveraging machine learning algorithms to analyze social media data from Twitter, Telegram, and Discord, enabling Big Data Protocol to get an accurate insight into market sentiment, better predict trends, and provide valuable market insights for all stakeholders.

The Skim AI team also built an AI model for:

Summarizing data and user interactions

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