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

Chao Li; Balaji Palanisamy; Runhua Xu; Jinlai Xu; Jingzhe Wang

doi:10.1145/3422337.3447845

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

23 Scopus citations

Abstract

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.

Original language	English
Title of host publication	CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy
Publisher	Association for Computing Machinery, Inc
Pages	113-118
Number of pages	6
ISBN (Electronic)	9781450381437
DOIs	https://doi.org/10.1145/3422337.3447845
State	Published - 26 Apr 2021
Externally published	Yes
Event	11th ACM Conference on Data and Application Security and Privacy, CODASPY 2021 - Virtual, Online, United States Duration: 26 Apr 2021 → 28 Apr 2021

Publication series

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

Conference

Conference	11th ACM Conference on Data and Application Security and Privacy, CODASPY 2021
Country/Territory	United States
City	Virtual, Online
Period	26/04/21 → 28/04/21

Keywords

blockchain
dataset
social network
steem

Access to Document

10.1145/3422337.3447845

Cite this

Li, C., Palanisamy, B., Xu, R., Xu, J., & Wang, J. (2021). SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform. In CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy (pp. 113-118). (CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy). Association for Computing Machinery, Inc. https://doi.org/10.1145/3422337.3447845

Li, Chao ; Palanisamy, Balaji ; Xu, Runhua et al. / SteemOps : Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform. CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy. Association for Computing Machinery, Inc, 2021. pp. 113-118 (CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy).

@inproceedings{611c2b00ad424f81b743203eff2ee8f5,

title = "SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform",

abstract = "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.",

keywords = "blockchain, dataset, social network, steem",

author = "Chao Li and Balaji Palanisamy and Runhua Xu and Jinlai Xu and Jingzhe Wang",

note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 11th ACM Conference on Data and Application Security and Privacy, CODASPY 2021 ; Conference date: 26-04-2021 Through 28-04-2021",

year = "2021",

month = apr,

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doi = "10.1145/3422337.3447845",

language = "英语",

series = "CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy",

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Li, C, Palanisamy, B, Xu, R, Xu, J & Wang, J 2021, SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform. in CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy. CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy, Association for Computing Machinery, Inc, pp. 113-118, 11th ACM Conference on Data and Application Security and Privacy, CODASPY 2021, Virtual, Online, United States, 26/04/21. https://doi.org/10.1145/3422337.3447845

SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform. / Li, Chao; Palanisamy, Balaji; Xu, Runhua et al.
CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy. Association for Computing Machinery, Inc, 2021. p. 113-118 (CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - SteemOps

T2 - 11th ACM Conference on Data and Application Security and Privacy, CODASPY 2021

AU - Li, Chao

AU - Palanisamy, Balaji

AU - Xu, Runhua

AU - Xu, Jinlai

AU - Wang, Jingzhe

PY - 2021/4/26

Y1 - 2021/4/26

N2 - 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.

AB - 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.

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DO - 10.1145/3422337.3447845

M3 - 会议稿件

AN - SCOPUS:85104960267

T3 - CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy

SP - 113

EP - 118

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

PB - Association for Computing Machinery, Inc

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ER -

Li C, Palanisamy B, Xu R, Xu J, Wang J. SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform. In CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy. Association for Computing Machinery, Inc. 2021. p. 113-118. (CODASPY 2021 - Proceedings of the 11th ACM Conference on Data and Application Security and Privacy). doi: 10.1145/3422337.3447845

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

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Keywords

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