## 2 Related Work
(2018) calculated user reputation scores through contract computations to represent the degree of information exchange between users, thus proposing a reputation-based evaluation mechanism. However, the implementation of smart contracts in such systems adds complexity, particularly in ensuring that reputation is calculated in an unbiased and accurate manner, which complicates the overall system design. [PERSON] et al. proposed \"SocialChain\" (2018), which contributes by providing a decentralized framework for social media, enhancing privacy and content ownership, but its main limitation is the lack of scalability and a robust incentivization model. [PERSON] et al. (2018) discusses how blockchain-based social media can mitigate issues like misinformation and centralized control, but also addresses challenges such as the scalability of integrating large social media datasets and ensuring user privacy within a decentralized structure. In blockchain systems, tokens are commonly employed as incentives for users. Adhering to the principles of token economics (2018), this model economically incentivizes constructive behaviors, such as generating contents, by rewarding with tokens (typically in the form of cryptocurrency), thus endowing users' knowledge participation activities with both social and economic dimensions (2018). However, cryptocurrencies pose significant risks to users due to their high volatility and the lesser degree of regulation compared to traditional financial markets, which is not suitable for providing a stable medium for transactions (2018). [PERSON] et al. (2018) identified and analyzed collusive behaviors among users in BOSMs. Real data for Steemit are used as a case study herein to examine the collusion of users in BOSMs, and two user collusion behaviors (group voting and vote buying) are defined and measured. [PERSON]'s research (2018) assessed the wealth distribution in BOSMs, and revealed the \"rich get richer\" phenomenon in Steemit, demonstrating the uneven distribution of wealth on the platform. [PERSON] et al. (2018) argued that token incentive mechanisms risk leading to a monopoly and dominance by a minority of users within the community. [PERSON] et al. (2018) proposed a Proof of Contribution consensus mechanism, which rewards users who contribute to the system in a non-monetary manner, thereby avoiding the pitfalls associated with token-based incentives. In this paper, to circumvent the issues arising from token-based incentive mechanisms, the NexoNet integrates a non-token incentive mechanism to encourage user participation, aiming to create a fair and valuable user-centric multiple incentive mechanism. In recent years, several consensus mechanisms have been introduced to enhance the efficiency, scalability, and trustworthiness of blockchain applications, including those used in social media. Proof of Reputation (PoR) (2018) assigns greater validation power to nodes with a proven reputation, making it particularly suitable for social media platforms where trust is central. However, this mechanism can lead to the concentration of validation power among a few highly reputable nodes, potentially centralizing the system. Proof of Participation and Fees (PoPF) (2018), on the other hand, rewards users based on their activity and the fees they generate, encouraging engagement in decentralized social media networks. While PoPF incentivizes participation, its reliance on fee structures may lead to inequity between users with different resource levels. Delegated Proof of Stake (DPoS) (2018), where token holders vote for validators, offers a democratic approach, but it may still result in the centralization of power among popular validators. This can be a drawback for social media platforms aiming for true decentralization. Lastly, Proof of History (PoH) (2018), as used by Solana, enhances transaction speed through timestamping, making it ideal for real-time social media applications. However, PoH is still relatively new, and its long-term stability and security require further validation.