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Title: Sentiment analysis and NFT transaction dynamics Authors:  Giorgia Rivieccio - Parthenope University (Italy) [presenting]
Giovanni De Luca - University of Naples Parthenope (Italy)
Abstract: A stunning paradigm of a benefit of technology is blockchain-based cryptocurrency art. In a world of digital art where everything can be freely copied and saved with a right-click, blockchain technology allowed for the creation of scarcity, promoting the expansion, bursting, and stability of the tumultuous market of artists, collectors, galleries, and curators. In this context, human coordination across Web3's financial, regulatory, and social norms is changing due to emerging market Non-Fungible Token (NFT). Despite their youth, NFTs have a \$50 billion market worth and are quickly becoming crucial components of ownership in the digital sphere. NFT markets are volatile and hard to speculate on, much like conventional equities markets. We intend to develop a novel model to analyze the transaction dynamics, including market sentiment. We have collected data about this last year from the platform to create a time-series of collectible (artwork) NFT transactions. We have then analyzed the univariate dynamics and studied the improvements in forecasting after including the co-movements with respect to cryptocurrency data, google trends data about NFT, and the sentiment scores from news extracted by Thomson Reuters concerning NFT textual data.