Source-linked AI summary
Incentivized Blockchain-based Social Media Platforms: A Case Study of Steemit
Chao Li, Balaji Palanisamy
TL;DR
The paper asks whether Steemit’s DPoS governance is genuinely decentralized and whether cryptocurrency rewards work as intended. Analyzing blockchain activity, it finds concentrated influence and suspected bot-related misuse of the reward system.
Problem
The study asks how decentralized Steemit’s witness governance is and whether users can misuse its cryptocurrency-driven rewards, including by buying votes from bots.
Source: §1 · p. 2Method
The authors empirically analyze Steemit’s blockchain operations and reward mechanisms, including witness elections, transfers, and votes.
Source: §1 · p. 1, §5 · p. 6, §5.3 · p. 8Results
More than 16% of transfers went to curators suspected of being bots, while witness seats showed low turnover and possible control by large shareholders.
Source: §1 · p. 2Takeaways & Limitations
The findings suggest DPoS may not be desirable for highly decentralized social media and that Steemit’s reward system is substantially misused.
Source: §1 · p. 2
Abstract
from arXiv · showhide
This paper presents an empirical analysis of Steemit, a key representative of the emerging incentivized social media platforms over Blockchains, to understand and evaluate the actual level of decentralization and the practical effects of cryptocurrency-driven reward system in these modern social media platforms. Similar to Bitcoin, Steemit is operated by a decentralized community, where 21 members are periodically elected to cooperatively operate the platform through the Delegated Proof-of-Stake (DPoS) consensus protocol. Our study performed on 539 million operations performed by 1.12 million Steemit users during the period 2016/03 to 2018/08 reveals that the actual level of decentralization in Steemit is far lower than the ideal level, indicating that the DPoS consensus protocol may not be a desirable approach for establishing a highly decentralized social media platform. In Steemit, users create contents as posts which get curated based on votes from other users. The platform periodically issues cryptocurrency as rewards to creators and curators of popular posts. Although such a reward system is originally driven by the desire to incentivize users to contribute to high-quality contents, our analysis of the underlying cryptocurrency transfer network on the blockchain reveals that more than 16% transfers of cryptocurrency in Steemit are sent to curators suspected to be bots and also finds the existence of an underlying supply network for the bots, both suggesting a significant misuse of the current reward system in Steemit. Our study is designed to provide insights on the current state of this emerging blockchain-based social media platform including the effectiveness of its design and the operation of the consensus protocols and the reward system.
1 INTRODUCTION
The paper evaluates Steemit’s decentralized operation and cryptocurrency-driven reward system using blockchain activity. It finds concentrated influence in witness elections and substantial suspected bot-related reward misuse.
1 INTRODUCTION
- Steemit combines public blockchain-stored posts and votes with cryptocurrency rewards for block producers, authors, and curators.Its 21 witnesses are elected by shareholders through DPoS.Source: §1 · p. 1
- The study analyzes over 539 million operations by 1.12 million users from 2016/03 to 2018/08 to investigate decentralization and reward-system behavior.Its questions include witness turnover and shareholder influence, reward correlates, and possible vote buying from bots.Source: §1 · p. 2
- Steemit’s actual decentralization is far below the ideal, with low witness turnover, possible control by large shareholders, and economic ties among top witnesses and electors.The authors conclude that DPoS may not be desirable for a highly decentralized social media platform.Source: §1 · p. 2
- More than 16% of cryptocurrency transfers in the dataset went to curators suspected of being bots, alongside an underlying bot supply network.Big shareholders delegate shares to bots to earn profit, and the authors describe the reward system as substantially misused.Source: §1 · p. 2
2 BACKGROUND
Steemit combines social-media functions with a blockchain that records user operations and rewards contributors. Its DPoS design uses shareholder votes to select witnesses who produce blocks.
2 BACKGROUND
- Users create, reply to, repost, and vote on posts, which are ranked by vote weight; the blockchain stores platform data and produces a block every three seconds.Steemit also records follower and witness-election actions, cryptocurrency transfers, and other operations.Source: §2 · p. 2
- DPoS elects 21 witnesses to produce blocks, reaching consensus within that group rather than across the entire network.Users can vote for up to 30 witnesses; the top 20 and one randomly assigned seat produce blocks.Source: §2 · p. 2
- Users’ votes are weighted by their Steemit shares, which they obtain by locking STEEM or SBD for Steem Power and vested shares.Invested funds are withdrawn in thirteen equal weekly portions.Source: §2 · pp. 2–3
- Steemit issues producer, author, and curation rewards, with post rewards divided according to votes received within seven days.In 2018/08, 75% of a post’s reward went to its author and the remainder was shared among its curators.Source: §2 · p. 3
3 DATASET AND PRELIMINARY RESULTS
The section describes the blockchain data collection and summarizes Steemit’s growth and operation patterns. The analysis covers user and operation growth, social activity, and witness-election participation.
3.1 Data collection
- The dataset contains 539,817,204 user operations by 1,120,166 users from 2016/03 to 2018/08, plus 121,619,828 virtual operations.The authors identified 36 user-operation types and 11 virtual-operation types.Source: §3.1 · p. 3
3.2 Preliminary results
- Steemit saw three robust growth periods, and monthly new-user increases strongly correlated with STEEM price changes.The periods were 2016/05–2016/07, 2017/04–2017/06, and 2017/11–2018/01.Source: §3.2 · p. 3, Figure 2 · p. 4
- Social operations were used most, with more than 21 million post votes in 2018/08; witness-election activity involved only thousands of voters per month.The authors note that low participation by electors and electees could affect decentralization.Source: §3.2 · pp. 3–4, Figure 3 · p. 4
4 DECENTRALIZATION IN STEEMIT
The section evaluates Steemit’s decentralization through its witness election process. It finds low turnover, influence from large shareholders, and economic ties among election stakeholders, placing actual decentralization below the ideal.
4.1 Decentralized platform operation
- The 21-member witness group operates Steemit, while ideal decentralization entails frequent membership updates, distinct interests, and limited decisive power for large shareholders.The authors also treat weak correlation between elections and value transfers as a sign of greater decentralization.Source: §4.1 · p. 4, §4 · p. 4
4.2 Analyzing witness election
- From months 12–30, the top 12 witnesses held at least 10 of 21 seats, while most top-30 witnesses maintained high attendance after joining the group.The witness-group heatmap covers the 30 months from 2016/03 to 2018/08.Source: §4.2 · pp. 4–5, Figure 5 · p. 5
- The top elector’s votes carried $19,800,000 in shares, all owned by a user who selected that elector as proxy, and the top elector’s 27 chosen witnesses entered the top 50.The figure shows weighted votes for the top 60 witnesses, including votes from the top 29 electors and a sum of all others.Source: §4.2 · p. 5, Figure 6 · p. 5
- Only two of the top 30 witnesses and three of the top 29 electors made no value transfers; the investigated stakeholders otherwise formed a network with economic interactions.The authors identify a Korean-user cluster connected to the rest of the network mainly through several community leaders.Source: §4.2 · pp. 5–6, Figure 7 · p. 6
4.3 Discussion
- Steemit’s witness committee is relatively centralized in practice, making DPoS election-based decentralization fragile and potentially less desirable than the ideal.The authors suggest limiting large stakeholders’ voting power as a quick response, while favoring consensus protocols that form committees without user elections.Source: §4.3 · p. 6
- The authors favor replacing election-based DPoS with protocols that form committees without user elections, citing Algorand’s Verifiable Random Functions as an example.They describe limiting large stakeholders’ voting power as a quicker way to address the symptoms.Source: §4.3 · p. 6
5 REWARD SYSTEM IN STEEMIT
The section examines Steemit’s cryptocurrency reward design, how author and curator rewards relate to user behavior, and evidence of suspected vote trading. It finds that reward incentives can be difficult to optimize and are being misused through suspected bot networks.
5.1 Reward system
- The reward pool assigns 75% of each post reward to its author and shares the remaining 25% among curators who voted within seven days.The reward pool was about 53,800 STEEM per day in 2018/08.Source: §5.1 · p. 6
5.2 Factors correlated with rewards
- Curation rewards favor early votes with low prior rshares, but a 30-minute penalty makes the best voting time difficult to determine.Voting after 30 minutes avoids the penalty; curators’ accumulated rshares peak at six seconds and again just after the 30-minute period.Source: §5.1 · p. 7, Figure 10 · p. 7, §5.2 · p. 8
- Author rewards positively correlate with followers, post counts, and VESTS, but the authors caution that these relationships do not imply causation.Many authors earning more than $10 had VESTS below the suggested 5-STEEM minimum for maintaining an account in a normal state.Source: §5.2 · pp. 7–8, Figure 8 · p. 7
5.3 Misuse of reward system
- 2,939,051 transfers (16.17% of all transfers) were followed by a recipient’s suspicious vote for the linked post within seven days.The top recipient performed this trade 113,068 times and earned nearly $1 million.Source: §5.3 · p. 8
- Suspected bot curators vote much earlier than the average, and the authors identify a supply network in which large shareholders delegate VESTS for periodic payments.The top supplier earned more than $1.5 million by delegating VESTS to suspected bot curators.Source: Figure 11 · p. 7, §5.3 · pp. 8–9, Figure 13 · p. 9
5.4 Discussion
- The authors argue that bots can sell voting power to users promoting posts, potentially placing valueless posts or spam on the front page.Because Steemit operates decentrally, no single entity can delete problematic front-page posts; the proposed detection approach may be evaded if clients pay in other cryptocurrencies.Source: §5.4 · p. 9
6 RELATED WORK
Prior work has examined social platforms and emerging blockchain-based social media from behavioral, computational, and platform-specific perspectives. The paper distinguishes its contribution as an empirical analysis of decentralization and rewards using blockchain operations.
6 RELATED WORK
- Studies of Reddit, Quora, and Stack Overflow examined user behavior, community interaction, and platform content or reputation patterns.The cited work includes a survey of research on Reddit [26].Source: §6 · p. 9
- Prior Steemit research examined first-post factors associated with rewards and simulated decentralized curation conditions and selfish behavior [19].The authors describe their study as the first rigorous empirical analysis of decentralization and reward features using underlying blockchain operations.Source: §6 · p. 10
7 CONCLUSION
The paper empirically analyzes Steemit’s decentralization and cryptocurrency reward system using 539 million operations from 1.12 million users between 2016/03 and 2018/08. It reports substantially lower-than-ideal decentralization and widespread reward-system misuse involving suspected bot curators and an underlying supply network.
7 CONCLUSION
- The analysis of 539 million operations by 1.12 million users finds Steemit’s actual decentralization far below the ideal and questions DPoS for highly decentralized social media.More than 16% of cryptocurrency transfers went to curators suspected to be bots, and the study found an underlying bot supply network.Source: §7 · p. 10