Abstract
This paper presents KazSAnDRA, a dataset developed for Kazakh sentiment analysis that is the first and largest publicly available dataset of its kind. KazSAnDRA comprises an extensive collection of 180,064 reviews obtained from various sources and includes numerical ratings ranging from 1 to 5, providing a quantitative representation of customer attitudes. The study also pursued the automation of Kazakh sentiment classification through the development and evaluation of four machine learning models trained for both polarity classification and score classification. Experimental analysis included evaluation of the results considering both balanced and imbalanced scenarios. The most successful model attained an F1-score of 0.81 for polarity classification and 0.39 for score classification on the test sets. The dataset and fine-tuned models are open access and available for download under the Creative Commons Attribution 4.0 International License (CC BY 4.0) through our GitHub repository.
Abstract (translated)
本文介绍了KazSAnDRA，一个为哈萨克斯坦情感分析而创建的数据集，是现有公共可用数据集中最大的一个。KazSAnDRA包括来自各种来源的广泛收集的180,064条评论，包括从1到5的数值评分，为客户态度提供了定量表示。研究还通过开发和评估四种针对极性和分数分类的机器学习模型，实现了对哈萨克斯坦情感分类的自动化。实验分析包括考虑平衡和不平衡场景的结果评估。最成功的模型在偏置和不平衡场景下的F1分数分别为0.81和0.39。数据集和预训练模型均通过 Creative Commons Attribution 4.0 International License (CC BY 4.0) 在GitHub存储库中公开访问并可下载。
URL
https://arxiv.org/abs/2403.19335
