Research Area:  Machine Learning
Deep learning--based models have surpassed classical machine learning--based approaches in various text classification tasks, including sentiment analysis, news categorization, question answering, and natural language inference. In this article, we provide a comprehensive review of more than 150 deep learning--based models for text classification developed in recent years, and we discuss their technical contributions, similarities, and strengths. We also provide a summary of more than 40 popular datasets widely used for text classification. Finally, we provide a quantitative analysis of the performance of different deep learning models on popular benchmarks, and we discuss future research directions.
Author(s) Name:  Shervin Minaee , Nal Kalchbrenner , Erik Cambria , Narjes Nikzad , Meysam Chenaghlu , Jianfeng Gao
Journal name:  ACM Computing Surveys
Publisher name:  ACM
Volume Information:  Volume 54,Issue 3,April 2022, Article No.: 62,pp 1–40
Paper Link:   https://dl.acm.org/doi/abs/10.1145/3439726