Deep Learning-based Text Classification: A Comprehensive Review

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.

Automated summary

This article provides a comprehensive review of over 150 deep learning-based models for text classification developed in recent years. It discusses their technical contributions, similarities, and strengths, as well as summarizes popular datasets used for text classification. The article also includes a quantitative analysis of the performance of different deep learning models on popular benchmarks and discusses future research directions.