README.md

metadata

task_categories:
  - text-classification
language:
  - vi

Dataset Card for ViSFD

1. Dataset Summary

UIT‑ViSFD is a Vietnamese smartphone‐feedback corpus for aspect‐based sentiment analysis. It contains 11,122 human‐annotated comments collected from a major e‑commerce platform, with 10 aspect categories and 3 sentiment polarities per comment (positive/neutral/negative). In this unified version, train/dev/test splits have been merged into one CSV with a type column indicating the split.

2. Supported Tasks and Metrics

• Primary Task: Multi‐aspect sentiment classification

• Metrics:

  • Accuracy (per‐aspect and overall)
  • Macro‑averaged F1 (per‐aspect and overall)

3. Languages

• Vietnamese

4. Dataset Structure

Column	Type	Description
comment	string	The raw user feedback text (Vietnamese).
n_star	int	Number of stars given by the user (1–5).
data_time	string	Timestamp when the comment was posted.
label	string	JSON‐encoded mapping from each of the 10 aspects to one of {negative, neutral, positive}.
type	string	Split: train / validation / test.
dataset	string	Always ViSFD (for provenance).

5. Data Fields

• comment (str): The raw consumer feedback.
• n_star (int): User rating (1–5).
• data_time (str): Posting date/time of the comment.
• label (str): A JSON object mapping each aspect to its polarity label.
• type (str): Which split the sample belongs to.
• dataset (str): Always ViSFD.

6. Usage

from datasets import load_dataset
import json

ds = load_dataset("visolex/visfd")

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

# Inspect one example
example = train[0]
labels = json.loads(example["label"])
print("Comment:", example["comment"])
print("Aspects ▶️", labels)

7. Source & Links

• Original GitHub (data & code) https://github.com/LuongPhan/UIT-ViSFD
• Conference Paper Phan et al. (2021), “SA2SL: From Aspect‑Based Sentiment Analysis to Social Listening System for Business Intelligence” 

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8. Contact Information

• Author: Luong Luc Phan et al.
• Institute: University of Information Technology – VNUHCM, Vietnam
• Email: 18521073@gm.uit.edu.vn

If any organization intends to use this dataset for commercial purposes, please contact us at 18521073@gm.uit.edu.vn.

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10. Licensing and Citation

License

Refer to the original repository’s LICENSE. If unspecified, assume CC BY 4.0.

How to Cite

Conference Paper

@InProceedings{10.1007/978-3-030-82147-0_53,
  author    = {Luc Phan, Luong and Pham, Phuc and Nguyen, Kim Thi-Thanh and Huynh, Sieu Khai
               and Nguyen, Tham Thi and Nguyen, Luan Thanh and Huynh, Tin Van and Nguyen, Kiet Van},
  title     = {SA2SL: From Aspect-Based Sentiment Analysis to Social Listening System for Business Intelligence},
  booktitle = {Knowledge Science, Engineering and Management},
  year      = {2021},
  publisher = {Springer International Publishing},
  pages     = {647--658},
  isbn      = {978-3-030-82147-0}
}