Identifying Networked Patterns in Memecoin Twitter Accounts Using Exponential Random Graph Modeling

Abstract

This study investigated the structure of memecoin communication on Twitter. We built a following–follower and mention–reply network by crawling more than 100 official memecoin Twitter accounts. We evaluated social networks using two approaches: by comparing the following–follower and actual communication networks in terms of mentions and conducting statistical tests to detect a relationship between the structural position of each memecoin in its network and market performance measures. The findings indicate that Dogecoin and ShibaInu served as information dissemination hubs. Despite their popularity for information dissemination on Twitter, memecoins’ mediating functions via mentions were underdeveloped. This finding points to the risk of the spread of false information on Twitter and a gap in user-side information verification capabilities. This study also adds to the body of evidence showing that memecoins can use Twitter to disseminate information designed to increase their profitability.