SEACrowd/prdect_id

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Citation text from the card

@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 da

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dataset_licence({ "id": "SEACrowd/prdect_id" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 0