Analyzing Preferential Attachment in Peer-to-Peer BITCOIN Networks

Abstract

Due to the anonymous and remote nature of Electronic Commerce (E-commerce), reviews of products and vendors left by previous customers have emerged as an integral part of most online transactions. The reviews may influence the decision of customers buying the product since E-commerce websites/services do not allow customers to validate and inspect products in-store. In this paper, we analyze data from two BITCOIN marketplaces which include transactions between marketplace users and the ratings of those transactions given by those users. In this analysis we create a synthetic network model with similar topological properties as the networks of the interactions of both marketplaces. The results of our analysis show an interesting phenomenon in which user ratings, which range from -10 to 10, converge to a value of approximately two as the number of a user's transactions increase. Finally, we suggest future work on our synthetic model to improve its agreement with the transaction networks in order to better understand how reviews influence user decisions on transactions.