Dynamic Crypto Currency Transaction Index Modelling Using Blockchain and Community Detection Method

Abstract

In this paper, we propose a macro online transaction trend analysis framework for global crypto currencies by utilizing the dynamic community detection method which is popular and hot in structure analysis of the complex network. The proposed framework includes two major schemas, firstly, method for choosing the representative crypto currencies by utilizing our proposed novel dynamic community detection algorithm, secondly, the dynamic global block-chain transaction situation awareness index model (DGBIM) to analyze and to reflect macro transaction trend of the global online crypto currencies is presented. Compared with classical and offline macro transaction analysis index like GBI, our proposed DGBI model yields fairly good results on huge amount of real crypto currency transaction data crawled from mainstream online trading markets such as “feixiaohao”, “okcoin”, and “Huobi”.