# The Application of Blockchain in Social Media: A Systematic Literature Review
## 6 Discussion  
### Research Question Answers  
1.1 The Different Methods and Techniques Proposed by Past Studies to Leverage Blockchain Technology in Social Media  
Due to its fast progress and consistent popularity, the combination of blockchain and social media platforms is a topic that has engendered substantial consideration by researchers in recent years. Many papers have scrutinized popular social media sites from innumerable viewpoints in suggesting solutions to existing issues. (a) Resolving Fake Content Problems  
The evolution of social media has modified how we observe and manage data. Social media is nowadays the principal way to get information for many people. Never has it been as simple to access and exchange content as it is today. Everyone can register one or more profiles in minutes, often while remaining anonymous. Social media sites incentivize people to interact with a simple push of a button, and activities are generally twisted in the process of incentivization. Humans might not continuously regulate data flow in certain situations, and bots (computers that autonomously broadcast and circulate content) are able to administer social media profiles. Fake articles have been augmented through social media groups such as WhatsApp, Facebook, YouTube, etc., and are published in the system more quickly than can be envisaged. There have been varied uses of fake news in different news reporting. Several blockchain systems have been proposed to stop this phenomenon (see Table 4). The studies cited here used different Blockchain components to build a model, with smart contracta being one of the most used elements. [PERSON] et al. [48] presented a location-aware blockchain-based news validation system. Their goal was to differentiate fake and fallacious data from authentic data. Authenticated archives are saved in a distributed blockchain, with a smart contract then developed using solidity language to build a simulated Ethereum network locally. The structure is joined with social media, and authenticated users approve the accuracy of content. In addition, all users are unidentified, allowing them to confirm any evidence without external pressure. After an assessment, the system contains two pointers to prove whether the article is real or fake. [PERSON] et al. [49] exploited the advantage of peer-to-peer networks to remove fictitious content on social media. The proposed system is based on the Ethereum  
Figure 8: Classification of selected studies. Blockchain and its smart contract functionality. It employs a rating system to check the credibility of the data. Verification has two phases, i.e., first finding the date and position engendering the NFT, then rating. [PERSON] et al. [58] presented a social media scheme to diffuse news. It is adjusted via an epidemic approach and a scale-free network. They applied a message authentication structure to detect the constancy of content and its origins based on a blockchain implemented using Ethereum-based smart contracts. The efficacy of this system was examined by an operating agent-based display with NetLogo software. [PERSON] et al. [64] produced a system to anticipate fake content based on a smart contract. The authors utilize a smart contract to calculate a trust index based on the message and group structures such as chart density, rank, group grade, and adequacy. Following the rating based on the trust index, the message is either accepted or rejected. [PERSON] et al. [67] introduced a scheme called PoT (proof of trustworthiness protocol) for distinguishing and blocking fake items and disinformation. An immutable list of the identified report that is cryptographically protected is apportioned as a distributed ledger among the peers. The chain code of protocol in charge of discovering fake items is distributed to all peers in the system. A smart contract is deployed to stock items in the blockchain. [PERSON] et al. [69] used Blockchain to design a technique to avoid fake check-ins in LBNSs (Location-Based Social Networks).