Abstract
Fake news has become extremely popular in recent years and is widely used in social networking. The Internet has enabled an unprecedented number and speed of news exchanges between users. With the exponential growth of social media, information spreads among individuals at an unprecedented amount and speed. Verifying the news has effective ways to combat misinformation. Facilitating online data verification is an effective strategy to deal with the often overwhelming amount of misinformation. AntiFake is a machine-learning-based system that relies solely on its content and enables simple, cost-effective, and time-efficient news verification. The system is equipped with professional integration tools. The developed system uses machine learning techniques to automatically identify fraudulent or misleading information, thereby contributing to establishing trust in published content efficiently and cost-effectively. The results show that the developed system is effective and efficient.
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