Sentiment analysis, which is a notably method in text mining, can be used to extract the sentiment from people’s opinion. It then provides us with valuable perception on a topic from the public’s attitude, which create more opportunities for deeper analysis and prediction.
The thesis aims to investigate public’s sentiment towards Bitcoin through analyzing 10 million Bitcoin related tweets and assigning sentiment points on tweets, then using sentiment fluctuation as a factor to predict future crypto fluctuation. Price prediction is achieved by using a machine learning model called Recurrent Neural Network which automatically learns the pattern and generate following results with memory. The analysis revels slight connection between sentiment and crypto currency and the Neural Network model showed a strong connection between sentiment score and future price prediction.
This thesis presents a novel approach of constructing a non-consensus based decentralized financial transaction processing model with a built-in efficient audit structure. The problem of decentralized inter-bank payment processing is used for the model design. The two key insights used in this work are (1) to utilize a majority signature based replicated storage protocol for transaction authorization, and (2) to construct individual self-verifiable audit trails for each node as opposed to a common Blockchain. Theoretical analysis shows that the model provides cryptographic security for transaction processing and the presented audit structure facilitates financial auditing of individual nodes in time independent of the number of transactions.
This thesis addresses the widespread questions asked of Bitcoin. Cryptocurrencies - decentralized ledgers of peer to peer transactions – have taken the world by storm, with Bitcoin leading the way by means of being the original, most valuable, and most popular. Despite this widespread use, skepticism remains as to what Bitcoin is and whether it counts as money. I first defend the framework that I use for understanding Social Objects, Searle’s X counts as Y in C formula, as money is undoubtedly a social object. I then argue that Smit et al.’s account of money, while useful, mistakenly identifies an essential characteristic of money, the relative ratio scale, as a feature. I therefore present an alternative account of money. I then explain why the most commonly held account of Bitcoin, the chain Definition fails, and why Bitcoin being a fictional substance is not a problem for Bitcoin being money. I then demonstrate Bitcoin’s compatibility with my alternative account, and from this conclude that Bitcoin is Money.