# The Application of Blockchain in Social Media: A Systematic Literature Review
## 6 Discussion
### Research Question Answers
The system initially employs Smart Contract to create a unique localization system. [PERSON] et al. [72] applied an Ethereum smart contract and employed the BFS algorithm to count the closeness of a user. [PERSON] et al. [79] presented Proof of Truthfulness (PoT), a blockchain-based model to warm against fictitious content. The model has three mechanisms, a publisher, management protocol, and a Smart contract for news, as well as a news blockchain. The items are saved in a Merkle tree. [PERSON] et al. [85] designed a structure called Provenator. The system keeps the metadata to check the veracity and origin of materials and, at the same time, assures its validity for later. Provenator utilizes smart contracts to maintain the origin state of the data inside Blockchain. \begin{table}
\begin{tabular}{c c} \hline \hline
**Reference** & **Proposed Model** \\ \hline
[46] & Blockchain and keyed watermarking-based framework \\
[47] & Architecture of blockchain-based fictitious detection system \\
[48] & Architecture to store validation records in the blockchain \\
[49] & Rating system to detect the authenticity of news \\
[50] & A secure and privacy-preserving method \\
[51] & A framework for safely sharing information at the peer level \\
[52] & Machine Learning-based model using Blockchain \\
[56] & AI with a Proof-of-Stake smart contract algorithm architecture \\
[57] & Blockchain with Text Mining (TM) algorithm \\
[58] & Social media news-spreading model \\
[61] & A blockchain and watermarking-based social media framework \\
[63] & TRUSTD, a blockchain and collective signature-based ecosystem \\
[64] & A smart contract-based technique to avert fake posts \\
[66] & WhistleBlower, a decentralized fake news detection platform \\
[67] & Proof of Trustworthiness (PoT) \\
[69] & Avoiding false check-ins in Location-Based Social Networks \\
[72] & Method using the concept of decentralization \\
[73] & A blockchain-based social media notarization method \\
[74] & A blockchain consensus called Proof of Credibility (PoC) \\
[75] & A public opinion communication model \\
[77] & Architecture using data mining as a consensus algorithm \\
[78] & A prototype to counter the dissemination of fake news \\
[79] & Proof of Truthfulness (PoT) for news verification \\
[85] & Provenator, a blockchain-based distributed application \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Proposed models for avoiding fake contents Another component used by many papers is the consensus protocol. [PERSON] et al. [46] recommended a framework for fixing the problem of bogus or malicious articles on social media through examining messaging structure. The structure is based on Blockchain and keyed watermarking. The study used a Hyperledger Fabric Blockchain and its consensus algorithm, Practical Byzantine Fault Tolerance (PBFT). This system enables checking the veracity and responsibility of published items. However, this model cannot handle the problem of a masquerade attack situation, such as spoofing another user's profile, and can be cracked. In addition, it cannot be used with social media messaging platforms due to its considerable operation ratio. [PERSON] et al. [50] designed a decentralized structure to avoid social bots by deploying a public PoW-based blockchain. Users can create a decentralized architecture, providing them with a safe environment and protecting their privacy. However, only the data from a neighbor can be received. To avoid social bots impacting users by receiving and propagating a hoax, users can exclusively include the credible neighbors in their contact group. [PERSON] et al. [78] suggest a model to address the standing issue of fake news. In this direction, they evaluated data produced on social media and built a model to identify fake news that can be efficiently installed with negligible upkeep using Byzantine Fault Tolerance (BFT) consensus. Users are detached from the consensus layer.