Bitcoin's Edge: Embedded Sentiment in Blockchain Transactional Data

--Cryptocurrency blockchains, beyond their primary role as distributed payment systems, are increasingly used to store and share arbitrary content, such as text messages and files. Although often non-financial, this hidden content can impact price movements by conveying private information, shaping sentiment, and influencing public opinion. However, current analyses of such data are limited in scope and scalability, primarily relying on manual classification or hand-crafted heuristics. In this work, we address these limitations by employing Natural Language Processing techniques to analyze, detect patterns, and extract public sentiment encoded within blockchain transactional data. Our findings shed light on a previously underexplored source of freely available, transparent, and immutable data and introduce blockchain sentiment analysis as a novel and robust framework for enhancing financial predictions in cryptocurrency markets. Incidentally, we discover an asymmetry between cryptocurrencies; Bitcoin has an informational advantage over Ethereum in that the sentiment embedded into transactional data is sufficient to predict its price movement. First introduced by the Bitcoin software [1], cryptocurrency blockchains are electronic payment systems that eliminate the need for centralized authorities, such as banks, to validate transactions. Due to their core principles -decentralization, the removal of intermediaries, transparency, and transaction security among others-blockchains have experienced exponential growth in popularity over the past two decades. However, beyond being simple financial transaction records, blockchains have evolved, due to their key feature of immutability, to serve as repositories for arbitrary content, including text messages, images, and, in some cases, controversial material [2], [3].