Predatory Journal Classification Using Machine Learning

摘要

The prevalence of predatory journals has become more severe recently as this is harmful to science and technology development. For scholars publish papers more effectively and avoid publishers for profits, this research used a machine learning method to identify the predatory journals. The features like text content and keywords of the collected journals' websites were extracted from mainstream predatory journal websites and normal journal websites. This research proposed a predatory journal classification system based on a new model. The results show that our model's recall rate exceeds 90%, ensuring that the journals submitted by the researchers are not predatory.