SEACrowd/prdect_id
收藏PRDECT-ID 数据集概述
数据集描述
PRDECT-ID 数据集是一个包含印度尼西亚产品评论数据的集合，这些评论数据带有情感和情绪标签。数据来源于印度尼西亚的一家大型电商平台 Tokopedia。数据集包含来自 29 个产品类别的评论，使用印度尼西亚语。每个产品评论都标注了单一情绪，即爱、快乐、愤怒、恐惧或悲伤。标注过程由一组标注者完成，他们遵循临床心理学专家创建的情绪标注标准。此外，还提取了与产品评论相关的其他属性，如位置、价格、总体评分、销售数量、总评论数和客户评分，以支持进一步的研究。
语言
- 印度尼西亚语 (ind)
支持的任务
- 情感分析
- 情绪分类
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 4.0 (cc-by-4.0)
引用
如果使用 PRDECT-ID 数据集，请引用以下文献：
@article{SUTOYO2022108554, title = {PRDECT-ID: Indonesian product reviews dataset for emotions classification tasks}, journal = {Data in Brief}, volume = {44}, pages = {108554}, year = {2022}, issn = {2352-3409}, doi = {https://doi.org/10.1016/j.dib.2022.108554}, url = {https://www.sciencedirect.com/science/article/pii/S2352340922007612}, author = {Rhio Sutoyo and Said Achmad and Andry Chowanda and Esther Widhi Andangsari and Sani M. Isa}, keywords = {Natural language processing, Text processing, Text mining, Emotions classification, Sentiment analysis}, abstract = {Recognizing emotions is vital in communication. Emotions convey additional meanings to the communication process. Nowadays, people can communicate their emotions on many platforms; one is the product review. Product reviews in the online platform are an important element that affects customers’ buying decisions. Hence, it is essential to recognize emotions from the product reviews. Emotions recognition from the product reviews can be done automatically using a machine or deep learning algorithm. Dataset can be considered as the fuel to model the recognizer. However, only a limited dataset exists in recognizing emotions from the product reviews, particularly in a local language. This research contributes to the dataset collection of 5400 product reviews in Indonesian. It was carefully curated from various (29) product categories, annotated with five emotions, and verified by an expert in clinical psychology. The dataset supports an innovative process to build automatic emotion classification on product reviews.} }
@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} }
