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.

中文翻译：

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基于自然语言处理和区块链方法的虚假媒体检测


基于计算机科学领域的最新技术和发展，社交媒体网络是人类生活的重要组成部分之一。这种环境已成为共享任何主题和每日报告的信息和新闻的著名平台，这是收集数据和数据传输的主要时代。这种环境有很多优点，但从另一个角度来看，存在大量虚假新闻和信息，误导读者和用户获取所需的信息。社交媒体信息缺乏可信信息和真实新闻是这个系统的巨大问题之一。为了克服这个问题，我们提出了一个针对区块链和自然语言处理（NLP）各个方面的集成系统，以应用机器学习技术来检测虚假新闻并更好地预测虚假用户帐户和帖子。强化学习技术应用于此过程。为了提高该平台的安全性，应用了去中心化的区块链框架，该框架提供了数字内容权威证明的轮廓。更具体地说，该系统的概念是开发一个安全平台来预测和识别社交媒体网络中的假新闻。