Given the recent developments and advancements in the software engineering field, the internetbased entertainment network is one of the most important aspects of human existence. This environment has established itself as a popular forum for exchanging information and news on all topics as well as daily reports, which is the major period for information collecting and transmission. There are a variety of advantages to this environment, but from another angle, there are a lot of false data and information that lead readers and clients astray while they are looking for the information they need. One of the major problems with this approach is the lack of reliable data and true new insight regarding internet entertainment data. To combat this problem, we have created an integrated framework for various block chain and normal language processing (NLP) components that applies AI techniques to recognize fake news and better anticipate fake client records and postings. This methodology uses the Support Learning approach. The decentralized block chain structure was used, which provides the framework of computerized contents authority verification, to work on this stage with regard to security. More specifically, the goal of this framework is to promote a secure environment for spotting and identifying fake news in online entertainment companies.