Web Mining for Estimating Regulatory Blockchain Readiness
This work addresses the need for automated regulatory assessment in blockchain and cryptocurrency domains, though it appears incremental as it applies existing web mining and clustering techniques to a new application area.
The authors tackled the problem of quantitatively estimating countries' regulatory stance on cryptocurrencies by proposing a computational model based on web mining and search engines, achieving very good performance in experimental validation.
The regulatory framework of cryptocurrencies (and, in general, blockchain tokens) is of paramount importance. This framework drives nearly all key decisions in the respective business areas. In this work, a computational model is proposed for quantitatively estimating the regulatory stance of countries with respect to cryptocurrencies. This is conducted via web mining utilizing web search engines. The proposed model is experimentally validated. In addition, unsupervised learning (clustering) is applied for better analyzing the automatically derived estimations. Overall, very good performance is achieved by the proposed algorithmic approach.