  Advancements in distributed ledger technologies are driving the rise of
blockchain-based social media platforms such as Steemit, where users interact
with each other in similar ways as conventional social networks. These
platforms are autonomously managed by users using decentralized consensus
protocols in a cryptocurrency ecosystem. The deep integration of social
networks and blockchains in these platforms provides potential for numerous
cross-domain research studies that are of interest to both the research
communities. However, it is challenging to process and analyze large volumes of
raw Steemit data as it requires specialized skills in both software engineering
and blockchain systems and involves substantial efforts in extracting and
filtering various types of operations. To tackle this challenge, we collect
over 38 million blocks generated in Steemit during a 45 month time period from
2016/03 to 2019/11 and extract ten key types of operations performed by the
users. The results generate SteemOps, a new dataset that organizes more than
900 million operations from Steemit into three sub-datasets namely (i)
social-network operation dataset (SOD), (ii) witness-election operation dataset
(WOD) and (iii) value-transfer operation dataset (VOD). We describe the dataset
schema and its usage in detail and outline possible future research studies
using SteemOps. SteemOps is designed to facilitate future research aimed at
providing deeper insights on emerging blockchain-based social media platforms.
