license: cc-by-4.0
language:
- ind
pretty_name: Prdect Id
task_categories:
- sentiment-analysis
- emotion-classification
tags:
- sentiment-analysis
- emotion-classification
PRDECT-ID Dataset is a collection of Indonesian product review data annotated with emotion and sentiment labels. The data were collected from one of the giant e-commerce in Indonesia named Tokopedia. The dataset contains product reviews from 29 product categories on Tokopedia that use the Indonesian language. Each product review is annotated with a single emotion, i.e., love, happiness, anger, fear, or sadness. The group of annotators does the annotation process to provide emotion labels by following the emotions annotation criteria created by an expert in clinical psychology. Other attributes related to the product review are also extracted, such as Location, Price, Overall Rating, Number Sold, Total Review, and Customer Rating, to support further research.
Languages
ind
Supported Tasks
Sentiment Analysis, Emotion Classification
Dataset Usage
Using datasets library
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/prdect_id", trust_remote_code=True)
Using seacrowd library
# Load the dataset using the default config
dset = sc.load_dataset("prdect_id", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("prdect_id"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
More details on how to load the seacrowd library can be found here.
Dataset Homepage
https://data.mendeley.com/datasets/574v66hf2v/1
Dataset Version
Source: 1.0.0. SEACrowd: 2024.06.20.
Dataset License
Creative Commons Attribution 4.0 (cc-by-4.0)
Citation
If you are using the Prdect Id dataloader in your work, please cite the following:
@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}
}