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Iyanuoluwa/YOSM

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Hugging Face2023-01-10 更新2024-03-04 收录
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资源简介:
--- annotations_creators: - expert-generated language_creators: - found language: - yo license: - unknown multilinguality: - monolingual size_categories: - 1K<n<10K source_datasets: - original tags: - movie reviews - nollywood task_categories: - text-classification task_ids: - sentiment-analysis --- # Dataset Card for YOSM ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** - **Repository:** [Iyanuoluwa/YOSM](https://github.com/IyanuSh/YOSM) - **Paper:** [A new Yorùbá Sentiment Corpus for Nigerian/Nollywood Movie Reviews](https://arxiv.org/pdf/2204.09711.pdf) - **Point of Contact:** [Iyanuoluwa Shode](mailto:shodei1@montclair.edu) ### Dataset Summary YOSM is the first Yorùbá sentiment corpus for Nollywood movie reviews. The reviews were collected from movie reviews websites - IMDB, Rotten Tomatoes, LetterboxD, Cinemapointer, and Nollyrated. ### Languages Yorùbá (ISO 639-1: yo) - the third most spoken indigenous African language with over 50 million speakers. ## Dataset Structure ### Data Instances An instance consists of a movie review and the corresponding class label. ### Data Fields - `yo_review`: A movie review in Yorùbá - `sentiment`: The label describing the sentiment of the movie review. ### Data Splits The YOSM dataset has 3 splits: _train_, _dev_, and _test_. Below are the statistics for Version 3.0.0 of the dataset. | Dataset Split | Number of Instances in Split | | ------------- | ------------------------------------------- | | Train | 800 | | Development | 200 | | Test | 500 | ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions
提供机构:
Iyanuoluwa
原始信息汇总

数据集概述

数据集名称

  • 名称: YOSM

数据集描述

  • 描述: YOSM是首个针对Nollywood电影评论的Yorùbá语情感语料库。该数据集收集自IMDB、Rotten Tomatoes、LetterboxD、Cinemapointer和Nollyrated等电影评论网站。

语言

  • 语言: Yorùbá (ISO 639-1: yo)

数据集结构

  • 数据实例: 每个实例包含一个电影评论及其对应的情感标签。
  • 数据字段:
    • yo_review: 电影评论,使用Yorùbá语。
    • sentiment: 描述电影评论情感的标签。
  • 数据分割:
    • 训练集: 800个实例
    • 开发集: 200个实例
    • 测试集: 500个实例

任务类别

  • 任务类别: 文本分类
  • 任务ID: 情感分析

数据集创建

  • 注释创建者: 专家生成
  • 语言创建者: 发现
  • 许可证: 未知
  • 多语言性: 单语种
  • 大小类别: 1K<n<10K
  • 源数据集: 原始
  • 标签: 电影评论, Nollywood

使用数据注意事项

  • 社会影响: 信息缺失
  • 偏见讨论: 信息缺失
  • 其他已知限制: 信息缺失

附加信息

  • 数据集管理者: 信息缺失
  • 许可信息: 信息缺失
  • 引用信息: 信息缺失
  • 贡献: 信息缺失
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