# Turkish Text Classification: From Lexicon Analysis to Bidirectional Transformer

arXiv: https://arxiv.org/abs/2104.11642 · HTML: https://mlsanity.com/paper/2104.11642/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Aug 2020.

## Built on by (most cited first, 1 of 1)

- [BabyBear: Cheap inference triage for expensive language models](https://mlsanity.com/paper/2205.11747/) (2022)

## Abstract (arXiv)

Text classification has seen an increased use in both academic and industry settings. Though rule based methods have been fairly successful, supervised machine learning has been shown to be most successful for most languages, where most research was done on English. In this article, the success of lexicon analysis, support vector machines, and extreme gradient boosting for the task of text classification and sentiment analysis are evaluated in Turkish and a pretrained transformer based classifier is proposed, outperforming previous methods for Turkish text classification. In the context of text classification, all machine learning models proposed in the article are domain-independent and do not require any task-specific modifications.