  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 paper, we provide a comprehensive review of more than 150 deep learning
based models for text classification developed in recent years, and 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 discuss future research
directions.
