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README.md

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----
-annotations_creators:
-- no-annotation
-language_creators:
-- found
-language:
-- vi
-license:
-- unknown
-multilinguality:
-- monolingual
-pretty_name: "Vietnamese Students\u2019 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](#table-of-contents)
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#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](https://www.researchgate.net/publication/329645066_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](https://github.com/albertvillanova) for adding this dataset.

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vietnamese_students_feedback.py

@@ -1,112 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""Vietnamese Students’ Feedback Corpus."""
-
-import datasets
-
-
-_CITATION = """\
-@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}
-}
-"""
-
-_DESCRIPTION = """\
-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.
-"""
-
-_HOMEPAGE = "https://sites.google.com/uit.edu.vn/uit-nlp/datasets-projects#h.p_4Brw8L-cbfTe"
-
-# TODO: Add the licence for the dataset here if you can find it
-# _LICENSE = ""
-
-_URLS = {
-    datasets.Split.TRAIN: {
-        "sentences": "https://drive.google.com/uc?id=1nzak5OkrheRV1ltOGCXkT671bmjODLhP&export=download",
-        "sentiments": "https://drive.google.com/uc?id=1ye-gOZIBqXdKOoi_YxvpT6FeRNmViPPv&export=down load",
-        "topics": "https://drive.google.com/uc?id=14MuDtwMnNOcr4z_8KdpxprjbwaQ7lJ_C&export=download",
-    },
-    datasets.Split.VALIDATION: {
-        "sentences": "https://drive.google.com/uc?id=1sMJSR3oRfPc3fe1gK-V3W5F24tov_517&export=download",
-        "sentiments": "https://drive.google.com/uc?id=1GiY1AOp41dLXIIkgES4422AuDwmbUseL&export=download",
-        "topics": "https://drive.google.com/uc?id=1DwLgDEaFWQe8mOd7EpF-xqMEbDLfdT-W&export=download",
-    },
-    datasets.Split.TEST: {
-        "sentences": "https://drive.google.com/uc?id=1aNMOeZZbNwSRkjyCWAGtNCMa3YrshR-n&export=download",
-        "sentiments": "https://drive.google.com/uc?id=1vkQS5gI0is4ACU58-AbWusnemw7KZNfO&export=download",
-        "topics": "https://drive.google.com/uc?id=1_ArMpDguVsbUGl-xSMkTF_p5KpZrmpSB&export=download",
-    },
-}
-
-
-class VietnameseStudentsFeedback(datasets.GeneratorBasedBuilder):
-    """Vietnamese Students’ Feedback Corpus."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "sentence": datasets.Value("string"),
-                    "sentiment": datasets.ClassLabel(names=["negative", "neutral", "positive"]),
-                    "topic": datasets.ClassLabel(names=["lecturer", "training_program", "facility", "others"]),
-                }
-            ),
-            homepage=_HOMEPAGE,
-            # license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download(_URLS)
-        return [
-            datasets.SplitGenerator(
-                name=split,
-                gen_kwargs={
-                    "sentences_path": data_dir[split]["sentences"],
-                    "sentiments_path": data_dir[split]["sentiments"],
-                    "topics_path": data_dir[split]["topics"],
-                },
-            ) for split in _URLS
-        ]
-
-    def _generate_examples(self, sentences_path, sentiments_path, topics_path):
-        with open(sentences_path, encoding="utf-8") as sentences, open(
-            sentiments_path, encoding="utf-8"
-        ) as sentiments, open(topics_path, encoding="utf-8") as topics:
-            for key, (sentence, sentiment, topic) in enumerate(zip(sentences, sentiments, topics)):
-                yield key, {
-                    "sentence": sentence.strip(),
-                    "sentiment": int(sentiment.strip()),
-                    "topic": int(topic.strip()),
-                }