Datasetpublic

visolex/VLSP2018-ABSA-Hotel

VLSP2018-ABSA-Hotel Dataset Summary The VLSP 2018 Hotel corpus is designed for Vietnamese Aspect-Based Sentiment Analysis (ABSA), covering two sub-tasks of Aspect Category Sentiment Analysis (ACSA): Aspect Category Detection (ACD): identify which Aspect#Category pairs are present in each review. Sentiment Polarity Classification (SPC): assign one of three sentiment labels (Positive, Negative, Neutral) to each detected Aspect#Category. This unified CSV contains 5… See the full description on the dataset page: https://huggingface.co/datasets/visolex/VLSP2018-ABSA-Hotel.

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Dataset Card

VLSP2018-ABSA-Hotel

Dataset Summary

The VLSP 2018 Hotel corpus is designed for Vietnamese Aspect-Based Sentiment Analysis (ABSA), covering two sub-tasks of Aspect Category Sentiment Analysis (ACSA):

1.Aspect Category Detection (ACD): identify which Aspect#Category pairs are present in each review.
2.Sentiment Polarity Classification (SPC): assign one of three sentiment labels (Positive, Negative, Neutral) to each detected Aspect#Category.

This unified CSV contains 5,600 reviews with a type column for train/dev/test and binary indicators for each aspect–category (0=no, 1=positive, 2=negative, 3=neutral).

Supported Tasks and Metrics

—Aspect Category Detection: multi-label classification
—Sentiment Polarity Classification: multi-class classification
—Metrics: Precision, Recall, F1 (for both ACD and SPC)

Languages

—Vietnamese

Dataset Structure

Column	Type	Description
`Review`	`str`	The raw hotel review text.
`<Aspect#Category>` (34 columns)	`int`	One-hot+polarity indicator per aspect#category (0/1/2/3).
`type`	`str`	Split: `train` / `validation` / `test`.
`dataset`	`str`	Always `VLSP2018-ABSA-Hotel`.

The 34 aspect–category columns are:

FACILITIES#CLEANLINESS, FACILITIES#COMFORT, …, SERVICE#GENERAL

(each value: 0=absent, 1=positive, 2=negative, 3=neutral)

Usage

python

from datasets import load_dataset

ds = load_dataset("visolex/vlsp2018-absa-hotel")

train = ds.filter(lambda ex: ex["type"] == "train")
val   = ds.filter(lambda ex: ex["type"] == "dev")
test  = ds.filter(lambda ex: ex["type"] == "test")

print(train[0])

Source & Links

—GitHub: https://github.com/ds4v/absa-vlsp-2018
—Publication: End-to-end Multi-task Solutions for ACSA on Vietnamese (VLSP 2018)

Citation

bibtex

@INPROCEEDINGS{9865479,
  author={Dang, Hoang-Quan and Nguyen, Duc-Duy-Anh and Do, Trong-Hop},
  booktitle={2022 IEEE International Conference on Cybernetics and Computational Intelligence (CyberneticsCom)}, 
  title={Multi-task Solution for Aspect Category Sentiment Analysis on Vietnamese Datasets}, 
  year={2022},
  volume={},
  number={},
  pages={404-409},
  keywords={Sentiment analysis;Analytical models;Computational modeling;Multitasking;Task analysis;Cybernetics;Computational intelligence;Aspect-based Sentiment Analysis;PhoBERT;Aspect Category Detection;Sentiment Polarity Classification},
  doi={10.1109/CyberneticsCom55287.2022.9865479}}
}