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Online Social Networking platforms are now more than ever part of people's everyday life. They often act as the medium through which people can communicate or discover engaging media. In recent years, thanks to the massive popularity gained by blockchain technology, a new generation of social media emerged. Steemit, one of the most well-known blockchain-based social networks, is based on the blockchain Steem. It employs the blockchain in two ways: as data storage, and to implement a rewarding mechanism for pieces of content that are relevant to the users. Employing a rewarding system based on the social activity of the users can have a strong impact on how people socialise. In this work, we study the interaction among the users of Steemit in terms of incremental patterns. In detail, we propose a set of incremental patterns, by using variants of patterns proposed in the literature and by defining a new pattern specifically thought for the scenario of Blockchain Online Social Media (BOSM). This paper's findings show that social interactions in BOSMs are highly conditioned by the presence of bots, and the patterns proposed can detect previously undetected complex interactions. |
