Abstract
Social media network is one of the important parts of human life based on the recent technologies and developments in terms of computer science area. This environment has become a famous platform for sharing information and news on any topics and daily reports, which is the main era for collecting data and data transmission. There are various advantages of this environment, but in another point of view there are lots of fake news and information that mislead the reader and user for the information needed. Lack of trust-able information and real news of social media information is one of the huge problems of this system. To overcome this problem, we have proposed an integrated system for various aspects of blockchain and natural language processing (NLP) to apply machine learning techniques to detect fake news and better predict fake user accounts and posts. The Reinforcement Learning technique is applied for this process. To improve this platform in terms of security, the decentralized blockchain framework applied, which provides the outline of digital contents authority proof. More specifically, the concept of this system is developing a secure platform to predict and identify fake news in social media networks.
Highlights
Variety of shared information is the realistic part of social media
PROPOSED FAKE NEWS DETECTION SYSTEM This section presents a detailed explanation of fake news detection with a combination of Natural Language Processing, Reinforcement Learning (RL) and blockchain
Based on the presented process, the solo raft and raft have the higher transaction latency comparing with adding solo ordering based on transport layer security (TLS), the cause the improvement in transparency and security of blockchain networks among peers
Summary
Variety of shared information is the realistic part of social media. From 2017, fake news has become a very considerable topic until now, which 365% frequently used online [1]. Along with the number of noisy and unstructured data, growth of the number of users, and news, there is a need for an automatic solution for extraction of fake news [13]–[15] These terms become limited based on the recent developments in machine learning, deep learning, and artificial intelligence. We collected the social media contents from Facebook and Twitter, which are famous information sharing platforms with thousands of users that upload millions of daily news and posts on various topics. Designing the fake news prevention system instead of a detection system and applying the Natural Language Processing (NLP) for the detailed text analysis based on the shared contents. Applying the proof of authority protocol and designing financial roots This process is the strong aspect of this system to find fake user information and accounts.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
