HausaNLP/Naija-Stopwords

---
license: cc-by-nc-sa-4.0
tags:
- sentiment analysis, Twitter, tweets
- stopwords
multilinguality:
- monolingual
- multilingual
language:
- hau
- ibo
- pcm
- yor
pretty_name: NaijaStopwords
---

# Naija-Stopwords

Naija-Stopwords is a part of the [Naija-Senti](https://huggingface.co/datasets/HausaNLP/NaijaSenti-Twitter) project. It is a list of collected stopwords from the four most widely spoken languages in Nigeria — Hausa, Igbo, Nigerian-Pidgin, and Yorùbá.

--------------------------------------------------------------------------------

## Dataset Description

- **Homepage:** https://github.com/hausanlp/NaijaSenti/tree/main/data/stopwords
- **Repository:** [GitHub](https://github.com/hausanlp/NaijaSenti/tree/main/data/stopwords)
- **Paper:** [NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis](https://aclanthology.org/2022.lrec-1.63/)
- **Leaderboard:** N/A
- **Point of Contact:** [Shamsuddeen Hassan Muhammad]([e-mail])

### Languages

4 most spoken Nigerian languages

* Hausa (hau)
* Igbo (ibo)
* Nigerian Pidgin (pcm)
* Yoruba (yor)

## Dataset Structure

### Data Instances

List of stopwords instances in each of the four language.

```
{
"word": "string"
}
```

### How to use it

```python
from datasets import load_dataset

# you can load specific languages (e.g., Hausa). This download train, validation and test sets.
ds = load_dataset("HausaNLP/Naija-Stopwords", "hau")

```

## Additional Information

### Dataset Curators

* Shamsuddeen Hassan Muhammad
* Idris Abdulmumin
* Ibrahim Said Ahmad
* Bello Shehu Bello

### Licensing Information

This Naija-Stopwords dataset is licensed under a Creative Commons Attribution BY-NC-SA 4.0 International License

### Citation Information

```
@inproceedings{muhammad-etal-2022-naijasenti,
title = "{N}aija{S}enti: A {N}igerian {T}witter Sentiment Corpus for Multilingual Sentiment Analysis",
author = "Muhammad, Shamsuddeen Hassan and
Adelani, David Ifeoluwa and
Ruder, Sebastian and
Ahmad, Ibrahim Sa{'}id and
Abdulmumin, Idris and
Bello, Bello Shehu and
Choudhury, Monojit and
Emezue, Chris Chinenye and
Abdullahi, Saheed Salahudeen and
Aremu, Anuoluwapo and
Jorge, Al{\'\i}pio and
Brazdil, Pavel",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.63",
pages = "590--602",
}
```

### Contributions

> This work was carried out with support from Lacuna Fund, an initiative co-founded by The Rockefeller Foundation, Google.org, and Canada’s International Development Research Centre. The views expressed herein do not necessarily represent those of Lacuna Fund, its Steering Committee, its funders, or Meridian Institute.

原始信息汇总

数据集概述

数据集名称

• Naija-Stopwords

数据集描述

• Naija-Stopwords 是 Naija-Senti 项目的一部分，收集了尼日利亚四种最广泛使用的语言的停用词：Hausa, Igbo, Nigerian-Pidgin, 和 Yorùbá。

数据集详情

• 许可证: cc-by-nc-sa-4.0
• 标签: sentiment analysis, Twitter, tweets, stopwords
• 多语言性: monolingual, multilingual
• 语言: hau, ibo, pcm, yor
• 美观名称: NaijaStopwords

数据集结构

• 数据实例: 包含四种语言的停用词列表。
• 数据格式: json { "word": "string" }

如何使用

python from datasets import load_dataset

加载特定语言（例如 Hausa）的数据集

ds = load_dataset("HausaNLP/Naija-Stopwords", "hau")

数据集语言

• Hausa (hau)
• Igbo (ibo)
• Nigerian Pidgin (pcm)
• Yoruba (yor)

许可证信息

• Naija-Stopwords 数据集根据 Creative Commons Attribution BY-NC-SA 4.0 International License 授权。

引用信息

bibtex @inproceedings{muhammad-etal-2022-naijasenti, title = "{N}aija{S}enti: A {N}igerian {T}witter Sentiment Corpus for Multilingual Sentiment Analysis", author = "Muhammad, Shamsuddeen Hassan and Adelani, David Ifeoluwa and Ruder, Sebastian and Ahmad, Ibrahim Sa{}id and Abdulmumin, Idris and Bello, Bello Shehu and Choudhury, Monojit and Emezue, Chris Chinenye and Abdullahi, Saheed Salahudeen and Aremu, Anuoluwapo and Jorge, Al{\i}pio and Brazdil, Pavel", booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference", month = jun, year = "2022", address = "Marseille, France", publisher = "European Language Resources Association", url = "https://aclanthology.org/2022.lrec-1.63", pages = "590--602", }