README.md

metadata

annotations_creators:
  - no-annotation
language_creators:
  - found
languages:
  - vi
licenses:
  - unknown
multilinguality:
  - monolingual
pretty_name: Vietnamese Students’ Feedback Corpus
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
  - topic-classification

Dataset Card for Vietnamese Students’ Feedback Corpus

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://sites.google.com/uit.edu.vn/uit-nlp/datasets-projects#h.p_4Brw8L-cbfTe
• Repository:
• Paper: UIT-VSFC: Vietnamese Students’ Feedback Corpus for Sentiment Analysis
• Leaderboard:
• Point of Contact:

Dataset Summary

Students’ feedback is a vital resource for the interdisciplinary research involving the combining of two different research fields between sentiment analysis and education.

Vietnamese Students’ Feedback Corpus (UIT-VSFC) is the resource consists of over 16,000 sentences which are human-annotated with two different tasks: sentiment-based and topic-based classifications.

To assess the quality of our corpus, we measure the annotator agreements and classification evaluation on the UIT-VSFC corpus. As a result, we obtained the inter-annotator agreement of sentiments and topics with more than over 91% and 71% respectively. In addition, we built the baseline model with the Maximum Entropy classifier and achieved approximately 88% of the sentiment F1-score and over 84% of the topic F1-score.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The language of the dataset text sentence is Vietnamese (vi).

Dataset Structure

Data Instances

An instance example:

{
  'sentence': 'slide giáo trình đầy đủ .', 
  'sentiment': 2, 
  'topic': 1
}

Data Fields

• sentence (str): Text sentence.
• sentiment: Sentiment class, with values 0 (negative), 1 (neutral) and 2 (positive).
• topic: Topic class, with values 0 (lecturer), 1 (training_program), 2 (facility) and 3 (others).

Data Splits

The dataset is split in train, validation and test.

	Tain	Validation	Test
Number of examples	11426	1583	3166

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

Unknown.

Citation Information

@InProceedings{8573337,
  author={Nguyen, Kiet Van and Nguyen, Vu Duc and Nguyen, Phu X. V. and Truong, Tham T. H. and Nguyen, Ngan Luu-Thuy},
  booktitle={2018 10th International Conference on Knowledge and Systems Engineering (KSE)},
  title={UIT-VSFC: Vietnamese Students’ Feedback Corpus for Sentiment Analysis},
  year={2018},
  volume={},
  number={},
  pages={19-24},
  doi={10.1109/KSE.2018.8573337}
}

Contributions

Thanks to @albertvillanova for adding this dataset.