DGurgurov/slovak_sa

该数据集包含一个用于斯洛伐克语言的情感分析数据集，来源于Pecar等人（2019）的研究。该数据集用于一个关于改进低资源语言词嵌入的项目。

原始信息汇总

数据集概述

数据集名称

Sentiment Analysis Data for the Slovak Language

数据集描述

该数据集包含由Pecar et al. (2019)提供的情感分析数据，用于研究斯洛伐克语言的情感分类。

数据结构

数据用于支持项目“通过图知识改进低资源语言的词嵌入”（improving word embeddings with graph knowledge for Low Resource Languages）。

许可证

MIT

任务类别

• 文本分类

语言

• 斯洛伐克语

引用信息

bibtex @inproceedings{pecar-etal-2019-improving, title = "Improving Sentiment Classification in {S}lovak Language", author = "Pecar, Samuel and Simko, Marian and Bielikova, Maria", editor = "Erjavec, Toma{v{z}} and Marci{ }czuk, Micha{l} and Nakov, Preslav and Piskorski, Jakub and Pivovarova, Lidia and {v{S}}najder, Jan and Steinberger, Josef and Yangarber, Roman", booktitle = "Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing", month = aug, year = "2019", address = "Florence, Italy", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/W19-3716", doi = "10.18653/v1/W19-3716", pages = "114--119", abstract = "Using different neural network architectures is widely spread for many different NLP tasks. Unfortunately, most of the research is performed and evaluated only in English language and minor languages are often omitted. We believe using similar architectures for other languages can show interesting results. In this paper, we present our study on methods for improving sentiment classification in Slovak language. We performed several experiments for two different datasets, one containing customer reviews, the other one general Twitter posts. We show comparison of performance of different neural network architectures and also different word representations. We show that another improvement can be achieved by using a model ensemble. We performed experiments utilizing different methods of model ensemble. Our proposed models achieved better results than previous models for both datasets. Our experiments showed also other potential research areas.", }