A Reputation System based on Blockchain and Deep Learning in Social Networks

Existing social networks, such as Twitter and Facebook, are rife with inaccurate and damaging information that is bad for society. Most existing solutions usually use deep learning models for disinformation detection in addition to artificial recognition. However, the result is easily tampered with by people. At the same time, if we strictly manage public opinions, freedom of speech will also cause controversy. In order to solve the above problems and maintain a good social network environment, we propose a new reputation mechanism based on blockchain and deep learning. To assess the reputation of message senders, our proposed mechanism utilizes smart contracts that automate programs without human intervention. Our approach avoids unduly restricting users' freedom of expression and instead employs deep learning models for rumor detection and sentiment analysis to identify and label messages. By controlling the dissemination of messages based on labels of messages and the sender's reputation, we aim to balance freedom of speech with social stability. Finally, we analyze the usability and performance of our proposed system.