Big data-driven english teaching for social media: a neural network-based approach

Big data and intelligence artificial have greatly broadened the channels for people to acquire knowledge. The practical application of artificial intelligence technology in college English classrooms can not only help teachers prepare more scientific and advanced teaching plans, and also effectively improve the quality of college English teaching. In this paper, we employ deep neural networks to design a big data-driven English teaching improvement scheme. The proposed method can help teachers and students improve teaching strategies and assist students to learn more accurately and efficiently. First, we analyze the current deficiencies and reasons in English teaching. Second, we analyze the application of artificial intelligence in text corpus construction. Third, we use neural networks to design an intelligent face recognition system for teachers to improve the attendance rate. Forth, by analyzing the students’ writing, we design a writing scoring method based on the neural network model, which can evaluate students’ writing content. Finally, we experimentally evaluate and verify the effectiveness of the proposed method in this paper.