Bitcoin Price Prediction and NFT Generator Based on Sentiment Analysis

Abstract

Twitter sentiment has been found to be useful in predicting whether the price of Bitcoin will rise or fall will climb or decline. Modelling market activity and hence emotion in the Bitcoin ecosystem gives insight into Bitcoin price forecasts. We take into account not just the emotion retrieved not just from tweets, but also from the quantity of tweets. With the goal of optimising time window within which expressed emotion becomes a credible predictor of price change, we provide data from research that examined the link among both sentiment and future price at various temporal granularities. We demonstrate in this study that not only can price direction be anticipated, but also the magnitude of price movement with same accuracy, and this is the study's major scientific contribution. Non-Fungible Token (NFT) has gained international interest in recent years as a blockchain-based application. The most prevalent kind of NFT that can be stored on many blockchains is digital art. We did studies on CryptoPunks, the most popular collection on the NFT market, in examine and depict each and every major ethical challenges. We investigated ethical concerns from three perspectives: design, trade transactions, and relevant Twitter topics. Using Python libraries, a Twitter crawler, and sentiment analysis tools, we scraped data from Twitter and performed the analysis and prediction on bitcoin and NFTs.