A Collaborative and Real-Time Model for Trusties Content in Social Media

Abstract Recently, social media is becoming a stronger tool for spreading news in the world. These platforms make it easy for anyone to disseminate their ideas, flood the world by different types of information. In order to minimize the inconvenience of fake news inundation, most of the developed techniques aim at detecting fake news by exploring how they propagate on the social media. Minimizing the negative effect of this kind of information, needs stronger mechanisms to detect fake news at an early stage by focusing on their contents. This paper proposes a new model for trusties’ content in social media. Its basic idea consists of combining news content and their propagation behavior over the social network. This model simulation shows that the susceptible fake news can be accused at an early stage. The performance evaluations show that the results are globally satisfactory.