Interaction Communities in Blockchain Online Social Media

Abstract

Surfing Online Social Media (OSM) websites have become a daily activity for a large number of people worldwide. People use OSMs to satisfy their innate need to socialise, but also as a source of information or to share personal facts. Thanks to the massive success of cryptocurrencies, the blockchain technology gained popularity among researchers, giving birth to a new generation of social media. Steemit is the most well-known blockchain-based social media, and it is based on the public blockchain Steem. Steemit employs Steem as data storage, and to implement a rewarding mechanism that grants cryptocurrency to pieces of content that are considered relevant by the users. Steem represents the first experiment that integrates OSMs and an economic rewarding system on the same platform, and in this paper, we inspect the interactions among the users from a community perspective. We apply two community detection algorithms on five graphs that model just as many facets of the Steem blockchain and test the detected structure against three measures for community structure evaluation. Findings show that communities tend to be very large, index of how much users are encouraged to interact as much as possible, and in particular, in the monetary graph, we detect a large number of the block producers of Steem.