KuBERT: Central Kurdish BERT Model and Its Application for Sentiment Analysis

Kozhin muhealddin Awlla, Hadi Veisi, Abdulhady Abas Abdullah
9/20/2025
cs.CLcs.AI

No confident code implementation found for this paper.

Abstract

This paper enhances the study of sentiment analysis for the Central Kurdish language by integrating the Bidirectional Encoder Representations from Transformers (BERT) into Natural Language Processing techniques. Kurdish is a low-resourced language, having a high level of linguistic diversity with minimal computational resources, making sentiment analysis somewhat challenging. Earlier, this was done using a traditional word embedding model, such as Word2Vec, but with the emergence of new language models, specifically BERT, there is hope for improvements. The better word embedding capabilities of BERT lend to this study, aiding in the capturing of the nuanced semantic pool and the contextual intricacies of the language under study, the Kurdish language, thus setting a new benchmark for sentiment analysis in low-resource languages.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Comparative Approaches to Sentiment Analysis Using Datasets in Major European and Arabic Languages

85% match2025

SemEval-2017 Task 4: Sentiment Analysis in Twitter using BERT

82% match1 repo42024

Fine-tuning Transformer-based Encoder for Turkish Language Understanding Tasks

82% match2024

Research on the Application of Deep Learning-based BERT Model in Sentiment Analysis

80% match2024

Ensembling Multilingual Transformers for Robust Sentiment Analysis of Tweets

80% match2025

Developing a Comprehensive Framework for Sentiment Analysis in Turkish

80% match2025

Cite this paper

@article{awlla2025kubert,
  title  = {KuBERT: Central Kurdish BERT Model and Its Application for Sentiment Analysis},
  author = {Kozhin muhealddin Awlla and Hadi Veisi and Abdulhady Abas Abdullah},
  year   = {2025},
  eprint = {2509.16804},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2509.16804v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2509.16804.svg)](https://codeofpaper.com/paper/2509.16804)

Discussion