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SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform

  • Chao Li
  • , Balaji Palanisamy
  • , Runhua Xu
  • , Jinlai Xu
  • , Jingzhe Wang
  • Beijing Jiaotong University
  • University of Pittsburgh
  • IBM

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

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.

源语言英语
主期刊名CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy
出版商Association for Computing Machinery, Inc
113-118
页数6
ISBN(电子版)9781450381437
DOI
出版状态已出版 - 26 4月 2021
已对外发布
活动11th ACM Conference on Data and Application Security and Privacy, CODASPY 2021 - Virtual, Online, 美国
期限: 26 4月 202128 4月 2021

丛书

姓名CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy

会议

会议11th ACM Conference on Data and Application Security and Privacy, CODASPY 2021
国家/地区美国
Virtual, Online
时期26/04/2128/04/21

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