Details
| Original language | English |
|---|---|
| Title of host publication | SIGIR 2022 |
| Subtitle of host publication | Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Pages | 3036-3045 |
| Number of pages | 10 |
| ISBN (electronic) | 9781450387323 |
| Publication status | Published - 7 Jul 2022 |
| Event | 45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022 - Madrid, Spain Duration: 11 Jul 2022 → 15 Jul 2022 |
Abstract
Social networks have become an inseparable part of human activities. Most existing social networks follow a centralized system model, which despite storing valuable information of users, arise many critical concerns such as content ownership and over-commercialization. Recently, decentralized social networks, built primarily on blockchain technology, have been proposed as a substitution to eliminate these concerns. Since decentralized architectures are mature enough to be on par with the centralized ones, decentralized social networks are becoming more and more popular. Decentralized social networks can offer both common options like writing posts and comments and more advanced options such as reward systems and voting mechanisms. They provide rich eco-systems for the influencers to interact with their followers and other users via staking systems based on cryptocurrency tokens. The vast and valuable data of the decentralized social networks open several new directions for the research community to extend human behavior knowledge. However, accessing and collecting data from these social networks is not easy because it requires strong blockchain knowledge, which is not the main focus of computer science and social science researchers. Hence, our work proposes the SoChainDB framework that facilitates obtaining data from these new social networks. To show the capacity and strength of SoChainDB, we crawl and publish Hive data - one of the largest blockchain-based social networks. We conduct extensive analyses to understand the insight of Hive data and discuss some interesting applications, e.g., game, non-fungible tokens market built upon Hive. It is worth mentioning that our framework is well-adaptable to other blockchain social networks with minimal modification. SoChainDB is publicly accessible at http: //sochaindb.com and the dataset is available under the CC BY-SA 4.0 license.
Keywords
- blockchain, database, datasets, decentralized applications, decentralized social networks, network analysis, social networks
ASJC Scopus subject areas
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
- Computer Science(all)
- Information Systems
- Computer Science(all)
- Software
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SIGIR 2022 : Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2022. p. 3036-3045.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - SoChainDB
T2 - 45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022
AU - Nguyen, Hoang H.
AU - Bozhkov, Dmytro
AU - Ahmadi, Zahra
AU - Nguyen, Nhat Minh
AU - Doan, Thanh Nam
N1 - Funding Information: This work was supported by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 833635 (project ROXANNE: Real-time network, text, and speaker analytics for combating organized crime, 2019-2022).
PY - 2022/7/7
Y1 - 2022/7/7
N2 - Social networks have become an inseparable part of human activities. Most existing social networks follow a centralized system model, which despite storing valuable information of users, arise many critical concerns such as content ownership and over-commercialization. Recently, decentralized social networks, built primarily on blockchain technology, have been proposed as a substitution to eliminate these concerns. Since decentralized architectures are mature enough to be on par with the centralized ones, decentralized social networks are becoming more and more popular. Decentralized social networks can offer both common options like writing posts and comments and more advanced options such as reward systems and voting mechanisms. They provide rich eco-systems for the influencers to interact with their followers and other users via staking systems based on cryptocurrency tokens. The vast and valuable data of the decentralized social networks open several new directions for the research community to extend human behavior knowledge. However, accessing and collecting data from these social networks is not easy because it requires strong blockchain knowledge, which is not the main focus of computer science and social science researchers. Hence, our work proposes the SoChainDB framework that facilitates obtaining data from these new social networks. To show the capacity and strength of SoChainDB, we crawl and publish Hive data - one of the largest blockchain-based social networks. We conduct extensive analyses to understand the insight of Hive data and discuss some interesting applications, e.g., game, non-fungible tokens market built upon Hive. It is worth mentioning that our framework is well-adaptable to other blockchain social networks with minimal modification. SoChainDB is publicly accessible at http: //sochaindb.com and the dataset is available under the CC BY-SA 4.0 license.
AB - Social networks have become an inseparable part of human activities. Most existing social networks follow a centralized system model, which despite storing valuable information of users, arise many critical concerns such as content ownership and over-commercialization. Recently, decentralized social networks, built primarily on blockchain technology, have been proposed as a substitution to eliminate these concerns. Since decentralized architectures are mature enough to be on par with the centralized ones, decentralized social networks are becoming more and more popular. Decentralized social networks can offer both common options like writing posts and comments and more advanced options such as reward systems and voting mechanisms. They provide rich eco-systems for the influencers to interact with their followers and other users via staking systems based on cryptocurrency tokens. The vast and valuable data of the decentralized social networks open several new directions for the research community to extend human behavior knowledge. However, accessing and collecting data from these social networks is not easy because it requires strong blockchain knowledge, which is not the main focus of computer science and social science researchers. Hence, our work proposes the SoChainDB framework that facilitates obtaining data from these new social networks. To show the capacity and strength of SoChainDB, we crawl and publish Hive data - one of the largest blockchain-based social networks. We conduct extensive analyses to understand the insight of Hive data and discuss some interesting applications, e.g., game, non-fungible tokens market built upon Hive. It is worth mentioning that our framework is well-adaptable to other blockchain social networks with minimal modification. SoChainDB is publicly accessible at http: //sochaindb.com and the dataset is available under the CC BY-SA 4.0 license.
KW - blockchain
KW - database
KW - datasets
KW - decentralized applications
KW - decentralized social networks
KW - network analysis
KW - social networks
UR - http://www.scopus.com/inward/record.url?scp=85135032629&partnerID=8YFLogxK
U2 - 10.1145/3477495.3531735
DO - 10.1145/3477495.3531735
M3 - Conference contribution
AN - SCOPUS:85135032629
SP - 3036
EP - 3045
BT - SIGIR 2022
Y2 - 11 July 2022 through 15 July 2022
ER -