SEACrowd/emotion_id_opinion

Emotion ID Opinion是一个包含7080条印尼语推文的数据集，每条推文都标注了六种情感标签：愤怒、恐惧、喜悦、爱、悲伤和中性。该数据集主要用于情感分类任务，支持使用`datasets`和`seacrowd`库进行加载。数据集的来源、版本、许可证和引用信息也都有详细说明。

Emotion ID Opinion is a dataset of Indonesian-language tweets conveying public opinion on a variety of topics. It contains 7080 Indonesian tweets and a persons emotion response towards each tweet. The data is annotated with six emotional labels, namely anger, fear, joy, love, sad, and neutral. The dataset is primarily used for emotion classification tasks and supports loading using the `datasets` and `seacrowd` libraries. The source, version, license, and citation information of the dataset are also detailed.

原始信息汇总

Emotion ID Opinion 数据集概述

数据集简介

Emotion ID Opinion 是一个包含印度尼西亚语推文的公开数据集，旨在捕捉公众对各种话题的情感反应。该数据集包含 7080 条印度尼西亚语推文，每条推文都标注了六种情感标签之一：愤怒、恐惧、喜悦、爱、悲伤和中性。

语言

• 印度尼西亚语

支持的任务

• 情感分类

数据集版本

• 源版本：1.0.0
• SEACrowd 版本：2024.06.20

数据集许可证

• Creative Commons Attribution Share-Alike 4.0 International

引用

如果使用 Emotion ID Opinion 数据集，请引用以下文献：

@article{RICCOSAN2022108465, title = {Emotion dataset from Indonesian public opinion}, journal = {Data in Brief}, volume = {43}, pages = {108465}, year = {2022}, issn = {2352-3409}, doi = {https://doi.org/10.1016/j.dib.2022.108465}, url = {https://www.sciencedirect.com/science/article/pii/S2352340922006588}, author = { Riccosan and Karen Etania Saputra and Galih Dea Pratama and Andry Chowanda}, keywords = {Emotion classification, Dataset, Tweet, Indonesia}, abstract = {An opinion is a type of judgment or a persons point of view about something. Twitter is a popular social media platform that includes a lot of public opinions and would be a suitable location to mine data in text form. With its vast population and active Twitter user base, Indonesia has the potential to be a source of opinion data mining. An opinion may be processed and result in the form of a persons emotional response towards something, such as whether they like, hate, love, or are happy about it. Upon that basis, a dataset of Indonesian-language tweets conveying public opinion on various topics was formed. The fact that there are only limited publicly available emotions text datasets in the Indonesian language supports our basis in this research to form our emotion dataset. The gathered data was cleaned and normalized in the pre-processing stage to the necessary form for study on the task of classifying emotions in Indonesian. The data collected is annotated with six emotional labels: anger, fear, joy, love, sad, and neutral.} }

@article{lovenia2024seacrowd, title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya}, year={2024}, eprint={2406.10118}, journal={arXiv preprint arXiv: 2406.10118} }