Survey text analysis has become an indispensable tool to organizations because they seek to unlock the full potential of open-ended survey responses.

This review article provides a thorough assessment of modern and innovative algorithms for text classification through both observational and experimental evaluations. We propose a new classification ...

The proposed algorithm first preprocesses news texts through tokenization, stop-word removal, and low-frequency word filtering to optimize text representation. Subsequently, the BiGRU model is ...

The proposed algorithm first preprocesses news texts through tokenization, stop-word removal, and low-frequency word filtering to optimize text representation. Subsequently, the BiGRU model is ...

This survey article is organized as follows: Section 2 describes extractive and abstractive rationalization approaches. Section 3 compiles a list of rationale-annotated data sets for text ...

In this survey, we have given an overview of natural language explanations, also called rationales, in explainable text classification. Throughout this survey, we have focussed on “annotator ...

Learn about the most effective text classification algorithms for NLP, and how to apply them to your data. Compare the pros and cons of different algorithms and find the best one for your problem.

I think it would be nice to have a tutorial that is basically the first thing that people look at when they want to figure out how to use ExplainaBoard on their own systems. The text classification ...