Information Flow and Social Organization in a Bitcoin Discussion Network on Twitter

Abstract

Abstract This study investigates the information flow and social organization in a Bitcoin discussion network on Twitter (BDN), using social network analysis to examine user‐user interactions. Results suggest that BDN presents a heterogenous degree distribution, where most users have few interactions. A myriad of weakly defined but well‐connected subcommunities enables efficient information flow in the network. BDN emanates a small‐world effect, without the dominance of a few influential users. “Star‐power agents,” such as Elon Musk, are popular references among users, but the network is driven bottom‐up by smaller “two‐sided” users. This explorative study demonstrates how the classification of different users can be used in analyzing online communities. Future research could compare the network structure of BDN with other networks and utilize sentiment analysis to analyze the quality of information.